From 7f184be2999617aad64f672a3badb83666bc3c73 Mon Sep 17 00:00:00 2001 From: vanithakattumuri Date: Fri, 31 May 2024 17:41:49 +0900 Subject: [PATCH] #2 updated the readtheDocs and CoMinePlus.py documentation --- PAMI/correlatedPattern/basic/CoMine.py | 36 ++++++- PAMI/correlatedPattern/basic/CoMinePlus.py | 101 +++++++++++------- .../PAMI.correlatedPattern.basic.doctree | Bin 119992 -> 129444 bytes .../correlatedPatternBasicCoMine.doctree | Bin 60904 -> 64226 bytes .../correlatedPatternBasicCoMinePlus.doctree | Bin 58575 -> 64674 bytes .../_build/doctrees/environment.pickle | Bin 8173996 -> 8176185 bytes .../html/PAMI.correlatedPattern.basic.html | 94 ++++++++++------ .../PAMI/correlatedPattern/basic/CoMine.html | 36 ++++++- .../correlatedPattern/basic/CoMinePlus.html | 101 +++++++++++------- .../html/correlatedPatternBasicCoMine.html | 16 ++- .../correlatedPatternBasicCoMinePlus.html | 78 ++++++++------ finalSphinxDocs/_build/html/searchindex.js | 2 +- 12 files changed, 317 insertions(+), 147 deletions(-) diff --git a/PAMI/correlatedPattern/basic/CoMine.py b/PAMI/correlatedPattern/basic/CoMine.py index 7d7023c7..d4085b59 100644 --- a/PAMI/correlatedPattern/basic/CoMine.py +++ b/PAMI/correlatedPattern/basic/CoMine.py @@ -300,13 +300,43 @@ def startMine(self) -> None: self.mine() def _maxSup(self, itemSet, item): + """ + Calculate the maximum support value for a given itemSet and item. + + :param itemSet: A set of items to compare. + :type itemSet: list or set + :param item: An individual item to compare. + :type item: Any + :return: The maximum support value from the itemSet and the individual item. + :rtype: float or int + """ sups = [self._mapSupport[i] for i in itemSet] + [self._mapSupport[item]] return max(sups) def _allConf(self, itemSet): + """ + Calculate the all-confidence value for a given itemSet. + + :param itemSet: A set of items for which to calculate the all-confidence. + :type itemSet: list or set + :return: The all-confidence value for the itemSet. + :rtype: float + """ return self._finalPatterns[itemSet] / max([self._mapSupport[i] for i in itemSet]) def recursive(self, item, nodes, root): + """ + Recursively build the tree structure for itemsets and find patterns that meet + the minimum support and all-confidence thresholds. + + :param item: The current item being processed. + :type item: Any + :param nodes: The list of nodes to be processed. + :type nodes: list of _Node + :param root: The root node of the current tree. + :type root: _Node + :return: None + """ if root.item is None: newRoot = _Node([item], 0, None) @@ -327,7 +357,7 @@ def recursive(self, item, nodes, root): itemCounts = {k:v for k, v in itemCounts.items() if v >= self._minSup} if len(itemCounts) == 0: return - + itemNodes = {} for transaction, count in transactions: transaction = [i for i in transaction if i in itemCounts] @@ -340,8 +370,8 @@ def recursive(self, item, nodes, root): itemNodes[item][0].add(node) itemNodes[item][1] += count - itemNodes = {k:v for k, v in sorted(itemNodes.items(), key=lambda x: x[1][1], reverse=True)} - + itemNodes = {k:v for k, v in sorted(itemNodes.items(), key=lambda x: x[1][1], reverse=True)} + for item in itemCounts: conf = itemNodes[item][1] / self._maxSup(newRoot.item, item) diff --git a/PAMI/correlatedPattern/basic/CoMinePlus.py b/PAMI/correlatedPattern/basic/CoMinePlus.py index ef5bb10d..2cf0af86 100644 --- a/PAMI/correlatedPattern/basic/CoMinePlus.py +++ b/PAMI/correlatedPattern/basic/CoMinePlus.py @@ -1,9 +1,8 @@ -# CoMine is one of the fundamental algorithm to discover correlated patterns in a transactional database. +# CoMinePlus is one of the fundamental algorithm to discover correlated patterns in a transactional database. # # **Importing this algorithm into a python program** -# -------------------------------------------------------- # -# from PAMI.correlatedPattern.basic import CoMine as alg +# from PAMI.correlatedPattern.basic import CoMinePlus as alg # # iFile = 'sampleTDB.txt' # @@ -11,13 +10,13 @@ # # minAllConf = 0.2 # can be specified between 0 and 1 # -# obj = alg.CoMine(iFile, minSup, minAllConf, sep) +# obj = alg.CoMinePlus(iFile, minSup, minAllConf, sep) # # obj.mine() # -# Rules = obj.getPatterns() +# frequentPatterns = obj.getPatterns() # -# print("Total number of Patterns:", len(Patterns)) +# print("Total number of Patterns:", len(frequentPatterns)) # # obj.save(oFile) # @@ -119,30 +118,30 @@ class CoMine(_ab._correlatedPatterns): About this algorithm ==================== - :**Description**: CoMine is one of the fundamental algorithm to discover correlated patterns in a transactional database. It is based on the traditional FP-Growth algorithm. This algorithm uses depth-first search technique to find all correlated patterns in a transactional database. + :**Description**: CoMinePlus is one of the fundamental algorithm to discover correlated patterns in a transactional database. It is based on the traditional FP-Growth algorithm. This algorithm uses depth-first search technique to find all correlated patterns in a transactional database. :**Reference**: Lee, Y.K., Kim, W.Y., Cao, D., Han, J. (2003). CoMine: efficient mining of correlated patterns. In ICDM (pp. 581–584). - :**parameters**: **iFile** (*str*) -- **Name of the Input file to mine complete set of correlated patterns** - **oFile** (*str*) -- **Name of the output file to store complete set of correlated patterns** - **minSup** (*int or float or str*) -- **The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.** - **minAllConf** (*float*) -- **The user can specify minAllConf values within the range (0, 1).** - **sep** (*str*) -- **This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.** - - :**Attributes**: **memoryUSS** (*float*) -- **To store the total amount of USS memory consumed by the program** - **memoryRSS** (*float*) -- **To store the total amount of RSS memory consumed by the program** - **startTime** (*float*) -- **To record the start time of the mining process** - **endTime** (*float*) -- **To record the completion time of the mining process** - **minSup** (*int*) -- **The user given minSup** - **minAllConf** (*float*) -- **The user given minimum all confidence Ratio(should be in range of 0 to 1)** - **Database** (*list*) -- **To store the transactions of a database in list** - **mapSupport** (*Dictionary*) -- **To maintain the information of item and their frequency** - **lno** (*int*) -- **it represents the total no of transactions** - **tree** (*class*) -- **it represents the Tree class** - **itemSetCount** (*int*) -- **it represents the total no of patterns** - **finalPatterns** (*dict*) -- **it represents to store the patterns** - **itemSetBuffer** (*list*) -- **it represents the store the items in mining** - **maxPatternLength** (*int*) -- **it represents the constraint for pattern length** + :**parameters**: - **iFile** (*str*) -- *Name of the Input file to mine complete set of correlated patterns.* + - **oFile** (*str*) -- *Name of the output file to store complete set of correlated patterns.* + - **minSup** (*int or float or str*) -- *The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.* + - **minAllConf** (*float*) -- *The user can specify minAllConf values within the range (0, 1).* + - **sep** (*str*) -- *This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.* + + :**Attributes**: - **memoryUSS** (*float*) -- *To store the total amount of USS memory consumed by the program.* + - **memoryRSS** (*float*) -- *To store the total amount of RSS memory consumed by the program.* + - **startTime** (*float*) -- *To record the start time of the mining process.* + - **endTime** (*float*) -- *To record the completion time of the mining process.* + - **minSup** (*int*) -- *The user given minSup.* + - **minAllConf** (*float*) -- *The user given minimum all confidence Ratio(should be in range of 0 to 1).* + - **Database** (*list*) -- *To store the transactions of a database in list.* + - **mapSupport** (*Dictionary*) -- *To maintain the information of item and their frequency.* + - **lno** (*int*) -- *it represents the total no of transactions.* + - **tree** (*class*) -- *it represents the Tree class.* + - **itemSetCount** (*int*) -- *it represents the total no of patterns.* + - **finalPatterns** (*dict*) -- *it represents to store the patterns.* + - **itemSetBuffer** (*list*) -- *it represents the store the items in mining.* + - **maxPatternLength** (*int*) -- *it represents the constraint for pattern length.* Execution methods ================= @@ -153,11 +152,11 @@ class CoMine(_ab._correlatedPatterns): Format: - (.venv) $ python3 CoMine.py + (.venv) $ python3 CoMinePlus.py Example Usage: - (.venv) $ python3 CoMine.py sampleTDB.txt output.txt 0.25 0.2 + (.venv) $ python3 CoMinePlus.py sampleTDB.txt output.txt 0.25 0.2 .. note:: minSup can be specified in support count or a value between 0 and 1. @@ -165,7 +164,7 @@ class CoMine(_ab._correlatedPatterns): .. code-block:: python - from PAMI.correlatedPattern.basic import CoMine as alg + from PAMI.correlatedPattern.basic import CoMinePlus as alg iFile = 'sampleTDB.txt' @@ -173,13 +172,13 @@ class CoMine(_ab._correlatedPatterns): minAllConf = 0.2 # can be specified between 0 and 1 - obj = alg.CoMine(iFile, minSup, minAllConf,sep) + obj = alg.CoMinePlus(iFile, minSup, minAllConf,sep) obj.mine() - patterns = obj.getPatterns() + frequentPatterns = obj.getPatterns() - print("Total number of Patterns:", len(patterns)) + print("Total number of Patterns:", len(frequentPatterns)) obj.savePatterns(oFile) @@ -200,7 +199,7 @@ class CoMine(_ab._correlatedPatterns): Credits ======= - The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran. + The complete program was written by B.Sai Chitra and revised by Tarun Sreepads under the supervision of Professor Rage Uday Kiran. """ @@ -294,20 +293,46 @@ def _convert(self, value: Union[int, float, str]) -> None: @deprecated("It is recommended to use 'mine()' instead of 'startMine()' for mining process. Starting from January 2025, 'startMine()' will be completely terminated.") def startMine(self) -> None: - """ - main method to start - """ self.mine() def _maxSup(self, itemSet, item): + """ + Calculate the maximum support value for a given itemSet and item. + + :param itemSet: A set of items to compare. + :type itemSet: list or set + :param item: An individual item to compare. + :type item: Any + :return: The maximum support value from the itemSet and the individual item. + :rtype: float or int + """ sups = [self._mapSupport[i] for i in itemSet] + [self._mapSupport[item]] return max(sups) def _allConf(self, itemSet): + """ + Calculate the all-confidence value for a given itemSet. + + :param itemSet: A set of items for which to calculate the all-confidence. + :type itemSet: list or set + :return: The all-confidence value for the itemSet. + :rtype: float + """ return self._finalPatterns[itemSet] / max([self._mapSupport[i] for i in itemSet]) def recursive(self, item, nodes, root): - + 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100644 --- a/finalSphinxDocs/_build/html/PAMI.correlatedPattern.basic.html +++ b/finalSphinxDocs/_build/html/PAMI.correlatedPattern.basic.html @@ -281,7 +281,21 @@

Submodules
recursive(item, nodes, root)[source]
-
+

Recursively build the tree structure for itemsets and find patterns that meet +the minimum support and all-confidence thresholds.

+
+
Parameters:
+
    +

  • item (Any) – The current item being processed.

    • +

  • nodes (list of _Node) – The list of nodes to be processed.

    • +

  • root (_Node) – The root node of the current tree.

    • +
+
+
Returns:
+

None

+
+
+
@@ -314,43 +328,47 @@

Submodules_correlatedPatterns

Description:
-

CoMine is one of the fundamental algorithm to discover correlated patterns in a transactional database. It is based on the traditional FP-Growth algorithm. This algorithm uses depth-first search technique to find all correlated patterns in a transactional database.

+

CoMinePlus is one of the fundamental algorithm to discover correlated patterns in a transactional database. It is based on the traditional FP-Growth algorithm. This algorithm uses depth-first search technique to find all correlated patterns in a transactional database.

Reference:

Lee, Y.K., Kim, W.Y., Cao, D., Han, J. (2003). CoMine: efficient mining of correlated patterns. In ICDM (pp. 581–584).

Parameters:
-

iFile (str) – Name of the Input file to mine complete set of correlated patterns -oFile (str) – Name of the output file to store complete set of correlated patterns -minSup (int or float or str) – The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count. -minAllConf (float) – The user can specify minAllConf values within the range (0, 1). -sep (str) – This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.

+
    +

  • iFile (str) – Name of the Input file to mine complete set of correlated patterns.

    • +

  • oFile (str) – Name of the output file to store complete set of correlated patterns.

    • +

  • minSup (int or float or str) – The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.

    • +

  • minAllConf (float) – The user can specify minAllConf values within the range (0, 1).

    • +

  • sep (str) – This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.

    • +
Attributes:
-

memoryUSS (float) – To store the total amount of USS memory consumed by the program -memoryRSS (float) – To store the total amount of RSS memory consumed by the program -startTime (float) – To record the start time of the mining process -endTime (float) – To record the completion time of the mining process -minSup (int) – The user given minSup -minAllConf (float) – The user given minimum all confidence Ratio(should be in range of 0 to 1) -Database (list) – To store the transactions of a database in list -mapSupport (Dictionary) – To maintain the information of item and their frequency -lno (int) – it represents the total no of transactions -tree (class) – it represents the Tree class -itemSetCount (int) – it represents the total no of patterns -finalPatterns (dict) – it represents to store the patterns -itemSetBuffer (list) – it represents the store the items in mining -maxPatternLength (int) – it represents the constraint for pattern length

+
    +

  • memoryUSS (float) – To store the total amount of USS memory consumed by the program.

    • +

  • memoryRSS (float) – To store the total amount of RSS memory consumed by the program.

    • +

  • startTime (float) – To record the start time of the mining process.

    • +

  • endTime (float) – To record the completion time of the mining process.

    • +

  • minSup (int) – The user given minSup.

    • +

  • minAllConf (float) – The user given minimum all confidence Ratio(should be in range of 0 to 1).

    • +

  • Database (list) – To store the transactions of a database in list.

    • +

  • mapSupport (Dictionary) – To maintain the information of item and their frequency.

    • +

  • lno (int) – it represents the total no of transactions.

    • +

  • tree (class) – it represents the Tree class.

    • +

  • itemSetCount (int) – it represents the total no of patterns.

    • +

  • finalPatterns (dict) – it represents to store the patterns.

    • +

  • itemSetBuffer (list) – it represents the store the items in mining.

    • +

  • maxPatternLength (int) – it represents the constraint for pattern length.

    • +

Terminal command

Format:
 
-(.venv) $ python3 CoMine.py <inputFile> <outputFile> <minSup> <minAllConf> <sep>
+(.venv) $ python3 CoMinePlus.py <inputFile> <outputFile> <minSup> <minAllConf> <sep>
 
 Example Usage:
 
-(.venv) $ python3 CoMine.py sampleTDB.txt output.txt 0.25 0.2
+(.venv) $ python3 CoMinePlus.py sampleTDB.txt output.txt 0.25 0.2
@@ -358,7 +376,7 @@

Submodules
from PAMI.correlatedPattern.basic import CoMine as alg
+
from PAMI.correlatedPattern.basic import CoMinePlus as alg
 
 iFile = 'sampleTDB.txt'
 
@@ -366,13 +384,13 @@ 
SubmodulesminAllConf = 0.2 # can  be specified between 0 and 1
 
-obj = alg.CoMine(iFile, minSup, minAllConf,sep)
+obj = alg.CoMinePlus(iFile, minSup, minAllConf,sep)
 
 obj.mine()
 
-patterns = obj.getPatterns()
+frequentPatterns = obj.getPatterns()
 
-print("Total number of  Patterns:", len(patterns))
+print("Total number of  Patterns:", len(frequentPatterns))
 
 obj.savePatterns(oFile)
 
@@ -391,9 +409,7 @@ 
Submodulesprint("Total ExecutionTime in seconds:", run)
 

 

-

-
The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran.

-

+
The complete program was written by B.Sai Chitra and revised by Tarun Sreepads under the supervision of Professor Rage Uday Kiran.

 

 

 getMemoryRSS() → float[source]

@@ -484,7 +500,21 @@ 
Submodules
 

 recursive(item, nodes, root)[source]

-

+
Recursively build the tree structure for itemsets and find patterns that meet
+the minimum support and all-confidence thresholds.

+

+
Parameters:

+
    
+
  • item (Any) – The current item being processed.
    • 
+
  • nodes (list of _Node) – The list of nodes to be processed.
    • 
+
  • root (_Node) – The root node of the current tree.
    • 
+

+

+
Returns:

+
None

+

+

+

@@ -503,7 +533,7 @@

Submodules
startMine() → None[source]
-

main method to start

+

Code for the mining process will start from this function

diff --git a/finalSphinxDocs/_build/html/_modules/PAMI/correlatedPattern/basic/CoMine.html b/finalSphinxDocs/_build/html/_modules/PAMI/correlatedPattern/basic/CoMine.html index 4f7a2451..d9035771 100644 --- a/finalSphinxDocs/_build/html/_modules/PAMI/correlatedPattern/basic/CoMine.html +++ b/finalSphinxDocs/_build/html/_modules/PAMI/correlatedPattern/basic/CoMine.html @@ -396,13 +396,43 @@

Source code for PAMI.correlatedPattern.basic.CoMine

self.mine()
def _maxSup(self, itemSet, item): + """ + Calculate the maximum support value for a given itemSet and item. + + :param itemSet: A set of items to compare. + :type itemSet: list or set + :param item: An individual item to compare. + :type item: Any + :return: The maximum support value from the itemSet and the individual item. + :rtype: float or int + """ sups = [self._mapSupport[i] for i in itemSet] + [self._mapSupport[item]] return max(sups) def _allConf(self, itemSet): + """ + Calculate the all-confidence value for a given itemSet. + + :param itemSet: A set of items for which to calculate the all-confidence. + :type itemSet: list or set + :return: The all-confidence value for the itemSet. + :rtype: float + """ return self._finalPatterns[itemSet] / max([self._mapSupport[i] for i in itemSet])
[docs] def recursive(self, item, nodes, root): + """ + Recursively build the tree structure for itemsets and find patterns that meet + the minimum support and all-confidence thresholds. + + :param item: The current item being processed. + :type item: Any + :param nodes: The list of nodes to be processed. + :type nodes: list of _Node + :param root: The root node of the current tree. + :type root: _Node + :return: None + """ if root.item is None: newRoot = _Node([item], 0, None) @@ -423,7 +453,7 @@

Source code for PAMI.correlatedPattern.basic.CoMine

itemCounts = {k:v for k, v in itemCounts.items() if v >= self._minSup} if len(itemCounts) == 0: return - + itemNodes = {} for transaction, count in transactions: transaction = [i for i in transaction if i in itemCounts] @@ -436,8 +466,8 @@

Source code for PAMI.correlatedPattern.basic.CoMine

itemNodes[item][0].add(node) itemNodes[item][1] += count - itemNodes = {k:v for k, v in sorted(itemNodes.items(), key=lambda x: x[1][1], reverse=True)} - + itemNodes = {k:v for k, v in sorted(itemNodes.items(), key=lambda x: x[1][1], reverse=True)} + for item in itemCounts: conf = itemNodes[item][1] / self._maxSup(newRoot.item, item) diff --git a/finalSphinxDocs/_build/html/_modules/PAMI/correlatedPattern/basic/CoMinePlus.html b/finalSphinxDocs/_build/html/_modules/PAMI/correlatedPattern/basic/CoMinePlus.html index f9f1fe15..76e1870c 100644 --- a/finalSphinxDocs/_build/html/_modules/PAMI/correlatedPattern/basic/CoMinePlus.html +++ b/finalSphinxDocs/_build/html/_modules/PAMI/correlatedPattern/basic/CoMinePlus.html @@ -94,12 +94,11 @@

Source code for PAMI.correlatedPattern.basic.CoMinePlus

-# CoMine is one of the fundamental algorithm to discover correlated patterns in a transactional database.
+# CoMinePlus is one of the fundamental algorithm to discover correlated patterns in a transactional database.
 #
 # **Importing this algorithm into a python program**
-# --------------------------------------------------------
 #
-#             from PAMI.correlatedPattern.basic import CoMine as alg
+#             from PAMI.correlatedPattern.basic import CoMinePlus as alg
 #
 #             iFile = 'sampleTDB.txt'
 #
@@ -107,13 +106,13 @@ 
Source code for PAMI.correlatedPattern.basic.CoMinePlus
#
 #             minAllConf = 0.2 # can  be specified between 0 and 1
 #
-#             obj = alg.CoMine(iFile, minSup, minAllConf, sep)
+#             obj = alg.CoMinePlus(iFile, minSup, minAllConf, sep)
 #
 #             obj.mine()
 #
-#             Rules = obj.getPatterns()
+#             frequentPatterns = obj.getPatterns()
 #
-#             print("Total number of  Patterns:", len(Patterns))
+#             print("Total number of  Patterns:", len(frequentPatterns))
 #
 #             obj.save(oFile)
 #
@@ -215,30 +214,30 @@ 
Source code for PAMI.correlatedPattern.basic.CoMinePlus
    About this algorithm
     ====================
 
-    :**Description**: CoMine is one of the fundamental algorithm to discover correlated  patterns in a transactional database. It is based on the traditional FP-Growth algorithm. This algorithm uses depth-first search technique to find all correlated patterns in a transactional database.
+    :**Description**: CoMinePlus is one of the fundamental algorithm to discover correlated  patterns in a transactional database. It is based on the traditional FP-Growth algorithm. This algorithm uses depth-first search technique to find all correlated patterns in a transactional database.
 
     :**Reference**: Lee, Y.K., Kim, W.Y., Cao, D., Han, J. (2003). CoMine: efficient mining of correlated patterns. In ICDM (pp. 581–584).
 
-    :**parameters**:    **iFile** (*str*) -- **Name of the Input file to mine complete set of correlated patterns**
-                        **oFile** (*str*) -- **Name of the output file to store complete set of correlated patterns**
-                        **minSup** (*int or float or str*) -- **The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.**
-                        **minAllConf** (*float*) -- **The user can specify minAllConf values within the range (0, 1).**
-                        **sep** (*str*) -- **This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.**
-
-    :**Attributes**:    **memoryUSS** (*float*) -- **To store the total amount of USS memory consumed by the program**
-                        **memoryRSS** (*float*) -- **To store the total amount of RSS memory consumed by the program**
-                        **startTime** (*float*) -- **To record the start time of the mining process**
-                        **endTime** (*float*) -- **To record the completion time of the mining process**
-                        **minSup** (*int*) -- **The user given minSup**
-                        **minAllConf** (*float*) -- **The user given minimum all confidence Ratio(should be in range of 0 to 1)**
-                        **Database** (*list*) -- **To store the transactions of a database in list**
-                        **mapSupport** (*Dictionary*) -- **To maintain the information of item and their frequency**
-                        **lno** (*int*) -- **it represents the total no of transactions**
-                        **tree** (*class*) -- **it represents the Tree class**
-                        **itemSetCount** (*int*) -- **it represents the total no of patterns**
-                        **finalPatterns** (*dict*) -- **it represents to store the patterns**
-                        **itemSetBuffer** (*list*) -- **it represents the store the items in mining**
-                        **maxPatternLength** (*int*) -- **it represents the constraint for pattern length**
+    :**parameters**:    - **iFile** (*str*) -- *Name of the Input file to mine complete set of correlated patterns.*
+                        - **oFile** (*str*) -- *Name of the output file to store complete set of correlated patterns.*
+                        - **minSup** (*int or float or str*) -- *The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.*
+                        - **minAllConf** (*float*) -- *The user can specify minAllConf values within the range (0, 1).*
+                        - **sep** (*str*) -- *This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.*
+
+    :**Attributes**:    - **memoryUSS** (*float*) -- *To store the total amount of USS memory consumed by the program.*
+                        - **memoryRSS** (*float*) -- *To store the total amount of RSS memory consumed by the program.*
+                        - **startTime** (*float*) -- *To record the start time of the mining process.*
+                        - **endTime** (*float*) -- *To record the completion time of the mining process.*
+                        - **minSup** (*int*) -- *The user given minSup.*
+                        - **minAllConf** (*float*) -- *The user given minimum all confidence Ratio(should be in range of 0 to 1).*
+                        - **Database** (*list*) -- *To store the transactions of a database in list.*
+                        - **mapSupport** (*Dictionary*) -- *To maintain the information of item and their frequency.*
+                        - **lno** (*int*) -- *it represents the total no of transactions.*
+                        - **tree** (*class*) -- *it represents the Tree class.*
+                        - **itemSetCount** (*int*) -- *it represents the total no of patterns.*
+                        - **finalPatterns** (*dict*) -- *it represents to store the patterns.*
+                        - **itemSetBuffer** (*list*) -- *it represents the store the items in mining.*
+                        - **maxPatternLength** (*int*) -- *it represents the constraint for pattern length.*
 
     Execution methods
     =================
@@ -249,11 +248,11 @@ 
Source code for PAMI.correlatedPattern.basic.CoMinePlus
      Format:
 
-      (.venv) $ python3 CoMine.py <inputFile> <outputFile> <minSup> <minAllConf> <sep>
+      (.venv) $ python3 CoMinePlus.py <inputFile> <outputFile> <minSup> <minAllConf> <sep>
 
       Example Usage:
 
-      (.venv) $ python3 CoMine.py sampleTDB.txt output.txt 0.25 0.2
+      (.venv) $ python3 CoMinePlus.py sampleTDB.txt output.txt 0.25 0.2
 
     .. note:: minSup can be specified in support count or a value between 0 and 1.
 
@@ -261,7 +260,7 @@ 
Source code for PAMI.correlatedPattern.basic.CoMinePlus
    .. code-block:: python
 
-            from PAMI.correlatedPattern.basic import CoMine as alg
+            from PAMI.correlatedPattern.basic import CoMinePlus as alg
 
             iFile = 'sampleTDB.txt'
 
@@ -269,13 +268,13 @@ 
Source code for PAMI.correlatedPattern.basic.CoMinePlus
            minAllConf = 0.2 # can  be specified between 0 and 1
 
-            obj = alg.CoMine(iFile, minSup, minAllConf,sep)
+            obj = alg.CoMinePlus(iFile, minSup, minAllConf,sep)
 
             obj.mine()
 
-            patterns = obj.getPatterns()
+            frequentPatterns = obj.getPatterns()
 
-            print("Total number of  Patterns:", len(patterns))
+            print("Total number of  Patterns:", len(frequentPatterns))
 
             obj.savePatterns(oFile)
 
@@ -296,7 +295,7 @@ 
Source code for PAMI.correlatedPattern.basic.CoMinePlus
    Credits
     =======
 
-             The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran.
+    The complete program was written by B.Sai Chitra and revised by Tarun Sreepads under the supervision of Professor Rage Uday Kiran.
 
     """
 
@@ -390,20 +389,46 @@ 
Source code for PAMI.correlatedPattern.basic.CoMinePlus
[docs]    @deprecated("It is recommended to use 'mine()' instead of 'startMine()' for mining process. Starting from January 2025, 'startMine()' will be completely terminated.")
     def startMine(self) -> None:
-        """
-        main method to start
-        """
         self.mine()

 
     def _maxSup(self, itemSet, item):
+        """
+        Calculate the maximum support value for a given itemSet and item.
+
+        :param itemSet: A set of items to compare.
+        :type itemSet: list or set
+        :param item: An individual item to compare.
+        :type item: Any
+        :return: The maximum support value from the itemSet and the individual item.
+        :rtype: float or int
+        """
         sups = [self._mapSupport[i] for i in itemSet] + [self._mapSupport[item]]
         return max(sups)
 
     def _allConf(self, itemSet):
+        """
+        Calculate the all-confidence value for a given itemSet.
+
+        :param itemSet: A set of items for which to calculate the all-confidence.
+        :type itemSet: list or set
+        :return: The all-confidence value for the itemSet.
+        :rtype: float
+        """
         return self._finalPatterns[itemSet] / max([self._mapSupport[i] for i in itemSet])
     
 
[docs]    def recursive(self, item, nodes, root):
-
+        """
+        Recursively build the tree structure for itemsets and find patterns that meet
+        the minimum support and all-confidence thresholds.
+
+        :param item: The current item being processed.
+        :type item: Any
+        :param nodes: The list of nodes to be processed.
+        :type nodes: list of _Node
+        :param root: The root node of the current tree.
+        :type root: _Node
+        :return: None
+        """
 
         newRoot = _Node(root.item + [item], 0, None)
 
diff --git a/finalSphinxDocs/_build/html/correlatedPatternBasicCoMine.html b/finalSphinxDocs/_build/html/correlatedPatternBasicCoMine.html
index 0db468f8..e537d938 100644
--- a/finalSphinxDocs/_build/html/correlatedPatternBasicCoMine.html
+++ b/finalSphinxDocs/_build/html/correlatedPatternBasicCoMine.html
@@ -296,7 +296,21 @@
 

 

 recursive(item, nodes, root)[source]

-

+
Recursively build the tree structure for itemsets and find patterns that meet
+the minimum support and all-confidence thresholds.

+

+
Parameters:

+
    
+
  • item (Any) – The current item being processed.
    • 
+
  • nodes (list of _Node) – The list of nodes to be processed.
    • 
+
  • root (_Node) – The root node of the current tree.
    • 
+

+

+
Returns:

+
None

+

+

+

 
 

 

diff --git a/finalSphinxDocs/_build/html/correlatedPatternBasicCoMinePlus.html b/finalSphinxDocs/_build/html/correlatedPatternBasicCoMinePlus.html
index 26ce1479..1a63bb5e 100644
--- a/finalSphinxDocs/_build/html/correlatedPatternBasicCoMinePlus.html
+++ b/finalSphinxDocs/_build/html/correlatedPatternBasicCoMinePlus.html
@@ -122,43 +122,47 @@
 
Bases: _correlatedPatterns

 

 
Description:

-
CoMine is one of the fundamental algorithm to discover correlated  patterns in a transactional database. It is based on the traditional FP-Growth algorithm. This algorithm uses depth-first search technique to find all correlated patterns in a transactional database.

+
CoMinePlus is one of the fundamental algorithm to discover correlated  patterns in a transactional database. It is based on the traditional FP-Growth algorithm. This algorithm uses depth-first search technique to find all correlated patterns in a transactional database.

 

 
Reference:

 
Lee, Y.K., Kim, W.Y., Cao, D., Han, J. (2003). CoMine: efficient mining of correlated patterns. In ICDM (pp. 581–584).

 

 
Parameters:

-
iFile (str) – Name of the Input file to mine complete set of correlated patterns
-oFile (str) – Name of the output file to store complete set of correlated patterns
-minSup (int or float or str) – The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.
-minAllConf (float) – The user can specify minAllConf values within the range (0, 1).
-sep (str) – This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.

+
    
+
  • iFile (str) – Name of the Input file to mine complete set of correlated patterns.
    • 
+
  • oFile (str) – Name of the output file to store complete set of correlated patterns.
    • 
+
  • minSup (int or float or str) – The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count.
    • 
+
  • minAllConf (float) – The user can specify minAllConf values within the range (0, 1).
    • 
+
  • sep (str) – This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.
    • 
+

 

 
Attributes:

-
memoryUSS (float) – To store the total amount of USS memory consumed by the program
-memoryRSS (float) – To store the total amount of RSS memory consumed by the program
-startTime (float) – To record the start time of the mining process
-endTime (float) – To record the completion time of the mining process
-minSup (int) – The user given minSup
-minAllConf (float) – The user given minimum all confidence Ratio(should be in range of 0 to 1)
-Database (list) – To store the transactions of a database in list
-mapSupport (Dictionary) – To maintain the information of item and their frequency
-lno (int) – it represents the total no of transactions
-tree (class) – it represents the Tree class
-itemSetCount (int) – it represents the total no of patterns
-finalPatterns (dict) – it represents to store the patterns
-itemSetBuffer (list) – it represents the store the items in mining
-maxPatternLength (int) – it represents the constraint for pattern length

+
    
+
  • memoryUSS (float) – To store the total amount of USS memory consumed by the program.
    • 
+
  • memoryRSS (float) – To store the total amount of RSS memory consumed by the program.
    • 
+
  • startTime (float) – To record the start time of the mining process.
    • 
+
  • endTime (float) – To record the completion time of the mining process.
    • 
+
  • minSup (int) – The user given minSup.
    • 
+
  • minAllConf (float) – The user given minimum all confidence Ratio(should be in range of 0 to 1).
    • 
+
  • Database (list) – To store the transactions of a database in list.
    • 
+
  • mapSupport (Dictionary) – To maintain the information of item and their frequency.
    • 
+
  • lno (int) – it represents the total no of transactions.
    • 
+
  • tree (class) – it represents the Tree class.
    • 
+
  • itemSetCount (int) – it represents the total no of patterns.
    • 
+
  • finalPatterns (dict) – it represents to store the patterns.
    • 
+
  • itemSetBuffer (list) – it represents the store the items in mining.
    • 
+
  • maxPatternLength (int) – it represents the constraint for pattern length.
    • 
+

 

 

 
Terminal command

 
Format:
 
-(.venv) $ python3 CoMine.py <inputFile> <outputFile> <minSup> <minAllConf> <sep>
+(.venv) $ python3 CoMinePlus.py <inputFile> <outputFile> <minSup> <minAllConf> <sep>
 
 Example Usage:
 
-(.venv) $ python3 CoMine.py sampleTDB.txt output.txt 0.25 0.2
+(.venv) $ python3 CoMinePlus.py sampleTDB.txt output.txt 0.25 0.2
 

 

 

@@ -166,7 +170,7 @@
 
minSup can be specified in support count or a value between 0 and 1.

 

 
Calling from a python program

-
from PAMI.correlatedPattern.basic import CoMine as alg
+
from PAMI.correlatedPattern.basic import CoMinePlus as alg
 
 iFile = 'sampleTDB.txt'
 
@@ -174,13 +178,13 @@
 
 minAllConf = 0.2 # can  be specified between 0 and 1
 
-obj = alg.CoMine(iFile, minSup, minAllConf,sep)
+obj = alg.CoMinePlus(iFile, minSup, minAllConf,sep)
 
 obj.mine()
 
-patterns = obj.getPatterns()
+frequentPatterns = obj.getPatterns()
 
-print("Total number of  Patterns:", len(patterns))
+print("Total number of  Patterns:", len(frequentPatterns))
 
 obj.savePatterns(oFile)
 
@@ -199,9 +203,7 @@
 print("Total ExecutionTime in seconds:", run)
 

 

-

-
The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran.

-

+
The complete program was written by B.Sai Chitra and revised by Tarun Sreepads under the supervision of Professor Rage Uday Kiran.

 

 

 getMemoryRSS() → float[source]

@@ -292,7 +294,21 @@
 

 

 recursive(item, nodes, root)[source]

-

+
Recursively build the tree structure for itemsets and find patterns that meet
+the minimum support and all-confidence thresholds.

+

+
Parameters:

+
    
+
  • item (Any) – The current item being processed.
    • 
+
  • nodes (list of _Node) – The list of nodes to be processed.
    • 
+
  • root (_Node) – The root node of the current tree.
    • 
+

+

+
Returns:

+
None

+

+

+

 
 

 

@@ -311,7 +327,7 @@
 

 

 startMine() → None[source]

-
main method to start

+
Code for the mining process will start from this function

 

 
 

diff --git a/finalSphinxDocs/_build/html/searchindex.js b/finalSphinxDocs/_build/html/searchindex.js
index d8e78974..47b4d360 100644
--- a/finalSphinxDocs/_build/html/searchindex.js
+++ b/finalSphinxDocs/_build/html/searchindex.js
@@ -1 +1 @@
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"frequentPatternCUDAcuECLATBit.rst", "frequentPatternCUDAcuECLATGCT.rst", "frequentPatternMaximalmaxFPGrowth.rst", "frequentPatternMining.rst", "frequentPatternPysparkParallelApriori.rst", "frequentPatternPysparkParallelECLAT.rst", "frequentPatternPysparkParallelFPGrowth.rst", "frequentPatternTopkFAE.rst", "frequentPatternWithMultipleMinimumSupport.rst", "frequentPatternclosedCHARM.rst", "fuzzyCorrelatedPatternMining.rst", "fuzzyCorrelatedPatternbasicFCPGrowth.rst", "fuzzyFrequentPatternMining.rst", "fuzzyFrequentPatternbasicFFIMiner.rst", "fuzzyGeoReferencedFrequentPatternMining.rst", "fuzzyGeoReferencedPeriodicFrequentPatternMining.rst", "fuzzyGeoreferencedFrequentPatternbasicFFSPMiner.rst", "fuzzyGeoreferencedPeriodicFrequentPatternbasicFGPFPMiner.rst", "fuzzyPatternMining.rst", "fuzzyPeriodicFrequentPatternMining.rst", "fuzzyPeriodicFrequentPatternbasicFPFPMiner.rst", "geoReferencedFrequentPatternMining.rst", "geoReferencedFrequentSequencePatternMining.rst", "geoReferencedPartialPeriodicPatternMining.rst", "geoReferencedPatternMining.rst", "geoReferencedPeriodicFrequentPatternMining.rst", "geoReferencedPeriodicFrequentPatternbasicGPFPMiner.rst", "georeferencedFrequentPatternbasicFSPGrowth.rst", "georeferencedFrequentPatternbasicSpatialECLAT.rst", "georeferencedPartialPeriodicPatternbasicSTEclat.rst", "highUtilityFrequentPatternBasicHUFIM.rst", "highUtilityFrequentPatternMining.rst", "highUtilityGeo-referencedFrequentPatternMining.rst", "highUtilityGeoreferencedFrequentPatternBasicSHUFIM.rst", "highUtilityPatternBasicEFIM.rst", "highUtilityPatternBasicHMiner.rst", "highUtilityPatternBasicUPGrowth.rst", "highUtilityPatternMining.rst", "highUtilitySpatialPatternBasicHDSHUIM.rst", "highUtilitySpatialPatternBasicSHUIM.rst", "highUtilitySpatialPatternMining.rst", "highUtilitySpatialPatternTopkTKSHUIM.rst", "index.rst", "localPeriodicPatternMining.rst", "localPeriodicPatternbasicLPPGrowth.rst", "localPeriodicPatternbasicLPPMBreadth.rst", "localPeriodicPatternbasicLPPMDepth.rst", "modules.rst", "multipleMinimumSupportBasedFrequentPatternBasicCFPGrowth.rst", "multipleMinimumSupportBasedFrequentPatternBasicCFPGrowthPlus.rst", "multiplePartialPeriodicPatternMining.rst", "multipleTimeseriesPatternMining.rst", "partialPeriodicFrequentPatternMining.rst", "partialPeriodicFrequentPatternbasicGPFgrowth.rst", "partialPeriodicFrequentPatternbasicPPF_DFS.rst", "partialPeriodicPatternInMultipleTimeSeriesPPGrowth.rst", "partialPeriodicPatternMining.rst", "partialPeriodicPatternbasicGThreePGrowth.rst", "partialPeriodicPatternbasicPPPGrowth.rst", "partialPeriodicPatternbasicPPP_ECLAT.rst", "partialPeriodicPatternclosedPPPClose.rst", "partialPeriodicPatternmaximalMax3PGrowth.rst", "partialPeriodicPatterntopkk3PMiner.rst", "periodicCorrelatedPatternMining.rst", "periodicCorrelatedPatternbasicEPCPGrowth.rst", "periodicFrequentPatternMining.rst", "periodicFrequentPatternbasicPFECLAT.rst", "periodicFrequentPatternbasicPFPGrowth.rst", "periodicFrequentPatternbasicPFPGrowthPlus.rst", "periodicFrequentPatternbasicPFPMC.rst", "periodicFrequentPatternbasicPSGrowth.rst", "periodicFrequentPatternclosedCPFPMiner.rst", "periodicFrequentPatternmaximalMaxPFGrowth.rst", "periodicFrequentPatterntopkTopkPFPTopkPFP.rst", "periodicFrequentPatterntopkkPFPMinerkPFPMiner.rst", "recurringPatternMining.rst", "recurringPatternbasicRPGrowth.rst", "relativeFrequent.rst", "relativeFrequentPattern.rst", "relativeFrequentPatternBasicRSFPGrowth.rst", "relativeHighUtilityPatternBasicRHUIM.rst", "relativeHighUtilityPatternMining.rst", "sequentialFrequentPatternMining.rst", "sequentialPatternMining.rst", "sequentialPatternMiningBasicSPADE.rst", "sequentialPatternMiningBasicSPAM.rst", "sequentialPatternMiningBasicprefixSpan.rst", "sequentialPatternMiningClosedbide.rst", "stablePeriodicFrequentPatternbasicSPPEclat.rst", "stablePeriodicFrequentPatternbasicSPPGrowth.rst", "stablePeriodicFrequentPatterntopKTSPIN.rst", "stablePeriodicPatternMining.rst", "temporalPatternMining.rst", "transactionalPatternMining.rst", "uncertainFrequentPatternBasicCUFPTree.rst", "uncertainFrequentPatternBasicPUFGrowth.rst", "uncertainFrequentPatternBasicTUFP.rst", "uncertainFrequentPatternBasicTubeP.rst", "uncertainFrequentPatternBasicTubeS.rst", "uncertainFrequentPatternBasicUFGrowth.rst", "uncertainFrequentPatternBasicUVECLAT.rst", "uncertainFrequentPatternMining.rst", "uncertainGeoReferencedFrequentPatternMining.rst", "uncertainGeoreferencedFrequentPatternBasicGFPGrowth.rst", "uncertainPatternMining.rst", "uncertainPeriodicFrequentPatternBasicUPFPGrowth.rst", "uncertainPeriodicFrequentPatternBasicUPFPGrowthPlus.rst", "uncertainPeriodicFrequentPatternMining.rst", "utilityPatternMining.rst", "weightedFrequentNeighbourhoodPatternBasicSWFPGrowth.rst", "weightedFrequentNeighbourhoodPatternMining.rst", "weightedFrequentPatternBasicWFIM.rst", "weightedFrequentPatternMining.rst", "weightedFrequentRegularPatternBasicWFRIMiner.rst", "weightedFrequentRegularPatternMining.rst"], "titles": ["Contiguous Frequent Patterns", "Correlated Pattern Mining", "Coverage Pattern Mining", "Fault-Tolerant Frequent Pattern Mining", "Frequent pattern With Multiple Minimum Support", "Fuzzy Correlated Pattern Mining", "Fuzzy Frequent Pattern Mining", "Fuzzy Geo-referenced Frequent Pattern Mining", "Fuzzy Geo-referenced Periodic Frequent Pattern Mining", "Fuzzy Periodic Frequent Pattern Mining", "Geo-referenced Frequent Pattern Mining", "Geo-referenced Frequent Sequence Pattern mining", "Geo-referenced Partial Periodic Pattern Mining", "Geo-referenced Periodic Frequent Pattern Mining", "High-Utility Frequent Pattern Mining", "High-Utility Geo-referenced Frequent Pattern Mining", "High-Utility Pattern mining", "High-Utility Spatial Pattern Mining", "Local Periodic Pattern Mining", "Multiple Partial Periodic Pattern Mining", "PAMI package", "PAMI.AssociationRules package", "PAMI.AssociationRules.basic package", "PAMI.correlatedPattern package", "PAMI.correlatedPattern.basic package", "PAMI.coveragePattern package", "PAMI.coveragePattern.basic package", "PAMI.extras package", "PAMI.extras.DF2DB package", "PAMI.extras.calculateMISValues package", "PAMI.extras.dbStats package", "PAMI.extras.fuzzyTransformation package", "PAMI.extras.generateDatabase package", "PAMI.extras.graph package", "PAMI.extras.image2Database package", "PAMI.extras.imageProcessing package", "PAMI.extras.messaging package", "PAMI.extras.neighbours package", "PAMI.extras.sampleDatasets package", "PAMI.extras.stats package", "PAMI.extras.syntheticDataGenerator package", "PAMI.extras.visualize package", "PAMI.faultTolerantFrequentPattern package", "PAMI.faultTolerantFrequentPattern.basic package", "PAMI.frequentPattern package", "PAMI.frequentPattern.basic package", "PAMI.frequentPattern.closed package", "PAMI.frequentPattern.cuda package", "PAMI.frequentPattern.maximal package", "PAMI.frequentPattern.pyspark package", "PAMI.frequentPattern.topk package", "PAMI.fuzzyCorrelatedPattern package", "PAMI.fuzzyCorrelatedPattern.basic package", "PAMI.fuzzyFrequentPattern package", "PAMI.fuzzyFrequentPattern.basic package", "PAMI.fuzzyGeoreferencedFrequentPattern package", "PAMI.fuzzyGeoreferencedFrequentPattern.basic package", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern package", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern.basic package", "PAMI.fuzzyPartialPeriodicPatterns package", "PAMI.fuzzyPartialPeriodicPatterns.basic package", "PAMI.fuzzyPeriodicFrequentPattern package", "PAMI.fuzzyPeriodicFrequentPattern.basic package", "PAMI.geoReferencedPeriodicFrequentPattern package", "PAMI.geoReferencedPeriodicFrequentPattern.basic package", "PAMI.georeferencedFrequentPattern package", "PAMI.georeferencedFrequentPattern.basic package", "PAMI.georeferencedFrequentSequencePattern package", "PAMI.georeferencedPartialPeriodicPattern package", "PAMI.georeferencedPartialPeriodicPattern.basic package", "PAMI.highUtilityFrequentPattern package", "PAMI.highUtilityFrequentPattern.basic package", "PAMI.highUtilityGeoreferencedFrequentPattern package", "PAMI.highUtilityGeoreferencedFrequentPattern.basic package", "PAMI.highUtilityPattern package", "PAMI.highUtilityPattern.basic package", "PAMI.highUtilityPattern.parallel package", "PAMI.highUtilityPatternsInStreams package", "PAMI.highUtilitySpatialPattern package", "PAMI.highUtilitySpatialPattern.basic package", "PAMI.highUtilitySpatialPattern.topk package", "PAMI.localPeriodicPattern package", "PAMI.localPeriodicPattern.basic package", "PAMI.multipleMinimumSupportBasedFrequentPattern package", "PAMI.multipleMinimumSupportBasedFrequentPattern.basic package", "PAMI.partialPeriodicFrequentPattern package", "PAMI.partialPeriodicFrequentPattern.basic package", "PAMI.partialPeriodicPattern package", "PAMI.partialPeriodicPattern.basic package", "PAMI.partialPeriodicPattern.closed package", "PAMI.partialPeriodicPattern.maximal package", "PAMI.partialPeriodicPattern.pyspark package", "PAMI.partialPeriodicPattern.topk package", "PAMI.partialPeriodicPatternInMultipleTimeSeries package", "PAMI.periodicCorrelatedPattern package", "PAMI.periodicCorrelatedPattern.basic package", "PAMI.periodicFrequentPattern package", "PAMI.periodicFrequentPattern.basic package", "PAMI.periodicFrequentPattern.closed package", "PAMI.periodicFrequentPattern.cuda package", "PAMI.periodicFrequentPattern.maximal package", "PAMI.periodicFrequentPattern.pyspark package", "PAMI.periodicFrequentPattern.topk package", "PAMI.periodicFrequentPattern.topk.TopkPFP package", "PAMI.periodicFrequentPattern.topk.kPFPMiner package", "PAMI.recurringPattern package", "PAMI.recurringPattern.basic package", "PAMI.relativeFrequentPattern package", "PAMI.relativeFrequentPattern.basic package", "PAMI.relativeHighUtilityPattern package", "PAMI.relativeHighUtilityPattern.basic package", "PAMI.sequence package", "PAMI.sequentialPatternMining package", "PAMI.sequentialPatternMining.basic package", "PAMI.sequentialPatternMining.closed package", "PAMI.stablePeriodicFrequentPattern package", "PAMI.stablePeriodicFrequentPattern.basic package", "PAMI.stablePeriodicFrequentPattern.topK package", "PAMI.subgraphMining package", "PAMI.subgraphMining.basic package", "PAMI.subgraphMining.topK package", "PAMI.uncertainFaultTolerantFrequentPattern package", "PAMI.uncertainFrequentPattern package", "PAMI.uncertainFrequentPattern.basic package", "PAMI.uncertainGeoreferencedFrequentPattern package", "PAMI.uncertainGeoreferencedFrequentPattern.basic package", "PAMI.uncertainPeriodicFrequentPattern package", "PAMI.uncertainPeriodicFrequentPattern.basic package", "PAMI.weightedFrequentNeighbourhoodPattern package", "PAMI.weightedFrequentNeighbourhoodPattern.basic package", "PAMI.weightedFrequentPattern package", "PAMI.weightedFrequentPattern.basic package", "PAMI.weightedFrequentRegularPattern package", "PAMI.weightedFrequentRegularPattern.basic package", "PAMI.weightedUncertainFrequentPattern package", "PAMI.weightedUncertainFrequentPattern.basic package", "Partial Periodic Frequent Pattern Mining", "Partial Periodic Pattern Mining", "Periodic correlated pattern mining", "Periodic Frequent Pattern Mining", "Recurring Pattern Mining", "Relative High-Utility Pattern Mining", "Sequential Frequent Pattern mining", "Stable Periodic Pattern Mining", "Uncertain Frequent Pattern mining", "Uncertain Geo-Referenced Frequent Pattern mining", "Uncertain Periodic Frequent Pattern mining", "Weighted Frequent Neighbourhood Pattern Mining", "Weighted Frequent Pattern Mining", "Weighted Frequent Regular Pattern Mining", "<no title>", "Contiguous Patterns", "CoMine", "CoMinePlus", "Basic", "CMine", "CPPG", "Basic", "FTApriori", "FTFPGrowth", "Basic", "Frequent Pattern mining", "Apriori", "ECLAT", "ECLATDiffset", "ECLATbitset", "FPGrowth", "cuApriori", "cuAprioriBit", "cudaAprioriGCT", 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263], "process": [2, 4, 7, 9, 10, 24, 26, 31, 35, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 142, 143, 149, 152, 153, 155, 156, 157, 158, 159, 161, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 185, 186, 188, 189, 191, 192, 193, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 254, 256, 257, 258, 260, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285, 286], "optim": [2, 4, 142, 143, 149, 157, 180, 254, 263, 286], "oper": [2, 43, 45, 75, 79, 84, 108, 119, 131, 157, 159, 166, 207, 210, 211, 220, 221, 251, 283], "improv": [2, 97, 157, 240], "effici": [2, 24, 26, 46, 54, 56, 58, 62, 66, 71, 75, 76, 97, 108, 113, 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148, 157, 176, 180, 191, 228, 237, 249, 250, 284], "approach": [3, 4, 5, 43, 45, 88, 91, 97, 113, 121, 123, 143, 159, 160, 166, 180, 182, 229, 230, 231, 238, 240, 241, 258, 263, 266], "aim": [3, 12, 16, 26, 73, 79, 80, 116, 138, 143, 155, 160, 195, 205, 209, 211, 213, 235, 260, 261, 263], "discov": [3, 7, 10, 11, 12, 14, 16, 24, 26, 43, 45, 46, 48, 49, 50, 52, 56, 60, 62, 66, 69, 73, 75, 76, 78, 79, 80, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 138, 139, 140, 143, 152, 153, 155, 156, 158, 159, 160, 162, 163, 165, 166, 174, 176, 177, 178, 179, 181, 183, 186, 188, 192, 193, 194, 195, 200, 201, 203, 205, 209, 210, 211, 213, 220, 225, 227, 229, 230, 231, 232, 233, 234, 235, 236, 237, 239, 240, 242, 243, 244, 245, 246, 247, 248, 252, 256, 257, 258, 260, 262, 263, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "larg": [3, 45, 56, 66, 79, 80, 90, 97, 98, 100, 104, 110, 160, 161, 162, 188, 200, 210, 213, 233, 240, 243, 244, 246, 252], "contain": [3, 10, 33, 71, 73, 75, 76, 79, 80, 110, 119, 144, 145, 146, 160, 193, 196, 202, 205, 206, 211, 213, 223, 252, 264, 265, 273, 274, 279, 280], "both": [3, 12, 80, 113, 138, 139, 160, 195, 213, 235, 237, 256], "uncertain": [3, 6, 40, 84, 121, 123, 125, 127, 135, 160, 184, 214, 220, 221, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 277, 278, 279], "record": [3, 24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 139, 152, 153, 155, 156, 158, 159, 160, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 220, 221, 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 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220, 221, 245, 252, 266, 275, 277, 278, 281, 283], "mine": [4, 20, 24, 26, 29, 31, 37, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 151, 152, 153, 155, 156, 157, 158, 159, 160, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 192, 193, 194, 195, 198, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 216, 217, 218, 220, 221, 222, 223, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 281, 282, 283, 284, 285, 286], "us": [4, 14, 15, 24, 26, 27, 29, 30, 31, 32, 33, 35, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 137, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 185, 188, 189, 190, 192, 198, 200, 201, 202, 203, 204, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "singl": [4, 45, 71, 75, 80, 110, 119, 120, 165, 180, 202, 206, 213, 252], "uniform": [4, 180, 264], "all": [4, 24, 26, 28, 30, 35, 39, 49, 54, 56, 58, 60, 62, 71, 73, 75, 78, 79, 80, 82, 84, 86, 89, 90, 91, 92, 106, 108, 110, 116, 119, 127, 152, 153, 155, 176, 178, 180, 185, 188, 189, 190, 192, 202, 205, 206, 207, 210, 211, 213, 216, 220, 221, 225, 226, 232, 233, 248, 249, 250, 251, 252, 260, 261, 264, 265, 276, 278], "vari": [4, 18, 136, 143, 145, 180, 215, 224, 263, 274, 280], "level": [4, 33, 101, 180], "By": [4, 180], "more": [4, 18, 66, 113, 143, 180, 200, 215, 256, 257, 258, 263, 264], "nuanc": [4, 180], "each": [4, 12, 14, 17, 19, 30, 39, 49, 73, 75, 79, 80, 82, 86, 113, 119, 139, 141, 145, 146, 176, 177, 178, 180, 190, 195, 203, 205, 208, 210, 211, 212, 213, 216, 217, 218, 222, 225, 226, 237, 249, 250, 253, 255, 256, 257, 264, 265, 274, 276, 279, 280], "evalu": [4, 180], "individu": [4, 180, 190, 276, 280], "its": [4, 17, 29, 30, 39, 54, 56, 58, 62, 82, 86, 113, 119, 136, 147, 149, 180, 185, 188, 189, 192, 212, 216, 217, 218, 224, 225, 257, 265, 280, 282, 286], "import": [4, 14, 15, 17, 24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 203, 204, 205, 206, 207, 208, 210, 211, 212, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 264, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "context": [4, 14, 15, 17, 139, 180, 203, 204, 212, 237], "traffic": [4, 8, 9, 19, 136, 137, 139, 143, 148, 180, 187, 191, 222, 224, 228, 237, 263, 284], "involv": [5, 7, 8, 9, 10, 11, 14, 15, 17, 19, 79, 137, 139, 141, 142, 144, 145, 146, 147, 148, 149, 182, 186, 187, 191, 193, 194, 203, 204, 210, 212, 222, 228, 237, 253, 254, 273, 274, 279, 282, 284, 286], "explor": [5, 71, 110, 113, 119, 182, 202, 252, 257], "itemset": [5, 45, 46, 48, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 86, 88, 91, 101, 110, 123, 129, 131, 133, 135, 141, 149, 165, 174, 181, 182, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 226, 229, 230, 252, 253, 255, 270, 272, 281, 283, 285, 286], "exhibit": [5, 7, 8, 9, 12, 136, 137, 138, 139, 143, 147, 149, 182, 186, 187, 191, 195, 224, 228, 235, 237, 263, 282, 286], "linear": [5, 182], "assess": [5, 182], "through": [5, 119, 123, 182, 270], "instead": [5, 182], "sole": [5, 138, 182, 235], "co": [5, 182], "strength": [5, 182], "uncov": [5, 182], "basket": [5, 14, 91, 101, 141, 148, 182, 203, 249, 250, 253, 284], "analyt": [5, 14, 104, 148, 149, 182, 203, 246, 284, 286], "financi": [5, 6, 9, 137, 140, 141, 143, 146, 182, 184, 191, 228, 247, 253, 263, 279], "ffp": [6, 184], "captur": [6, 8, 136, 184, 187, 224], "inher": [6, 184], "partial": [6, 60, 69, 86, 88, 89, 90, 91, 92, 101, 184, 195, 196, 201, 214, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 233, 234, 264], "event": [6, 8, 9, 10, 11, 12, 13, 15, 17, 19, 82, 136, 139, 142, 145, 147, 184, 187, 191, 193, 194, 195, 197, 204, 212, 216, 217, 218, 222, 223, 224, 237, 254, 274, 282], "requir": [6, 40, 73, 75, 136, 184, 205, 208, 224], "variat": [6, 12, 137, 184, 195, 228], "degre": [6, 136, 137, 184, 224, 228], "membership": [6, 54, 184, 185], "similar": [6, 184, 196], "them": [6, 113, 119, 137, 143, 184, 228, 257, 263], "suitabl": [6, 143, 184, 263], "imprecis": [6, 8, 9, 184, 187, 191], "medic": [6, 16, 184, 209], "qualiti": [6, 184], "control": [6, 26, 82, 86, 97, 98, 100, 101, 103, 108, 155, 156, 184, 216, 217, 218, 225, 226, 238, 239, 240, 241, 242, 243, 244, 245, 251], "geograph": [7, 8, 10, 11, 13, 145, 186, 187, 193, 194, 197, 274], "mai": [7, 9, 12, 13, 18, 19, 120, 136, 137, 143, 145, 146, 186, 191, 195, 197, 215, 222, 224, 228, 263, 264, 274, 279], "object": [7, 27, 28, 29, 30, 32, 33, 35, 36, 37, 39, 40, 41, 49, 52, 80, 82, 86, 91, 97, 101, 116, 119, 120, 147, 178, 183, 186, 190, 213, 216, 225, 242, 261, 276, 280, 282], "epidemiolog": [7, 8, 186, 187], "environment": [7, 8, 10, 11, 12, 13, 15, 136, 144, 146, 147, 186, 187, 193, 194, 195, 197, 204, 224, 273, 279, 282], "monitor": [7, 8, 10, 11, 12, 13, 15, 19, 136, 137, 138, 139, 142, 146, 147, 186, 187, 193, 194, 195, 197, 204, 222, 224, 228, 235, 237, 254, 279, 282], "recur": [8, 9, 12, 13, 19, 106, 136, 137, 138, 139, 187, 191, 195, 197, 214, 222, 224, 228, 235, 237, 247, 248, 264], "tempor": [8, 9, 10, 11, 12, 13, 18, 28, 31, 32, 40, 62, 79, 86, 88, 89, 90, 91, 92, 95, 97, 98, 100, 103, 104, 116, 127, 136, 138, 139, 187, 190, 191, 192, 193, 194, 195, 196, 197, 210, 214, 215, 223, 224, 225, 229, 230, 232, 233, 234, 235, 236, 237, 238, 240, 242, 243, 244, 245, 246, 260, 261, 276, 277, 278, 280], "locat": [8, 10, 15, 145, 187, 193, 196, 204, 274], "repetit": [8, 136, 143, 187, 224, 263], "natur": [8, 9, 123, 138, 145, 187, 191, 235, 268, 269, 274, 280], "phenomena": [8, 11, 13, 139, 187, 194, 197, 237], "over": [8, 18, 80, 119, 136, 138, 139, 142, 143, 187, 196, 213, 215, 223, 224, 235, 237, 254, 263], "time": [8, 9, 11, 12, 13, 18, 24, 26, 28, 30, 32, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 137, 138, 139, 140, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 187, 188, 189, 191, 192, 194, 195, 196, 197, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 215, 216, 217, 218, 220, 221, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 251, 252, 254, 256, 257, 258, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "space": [8, 12, 24, 26, 27, 29, 30, 31, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 187, 188, 189, 190, 192, 195, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "while": [8, 11, 43, 64, 66, 69, 75, 82, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 158, 159, 187, 194, 198, 200, 201, 208, 216, 217, 218, 227, 229, 230, 231, 232, 233, 236, 240, 241, 242, 243, 244, 248, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 281, 283, 285], "entiti": [8, 187], "flow": [8, 143, 187, 263], "studi": [8, 187], "character": [9, 14, 15, 18, 138, 191, 203, 204, 215, 235], "seri": [9, 11, 18, 28, 30, 93, 97, 106, 137, 140, 191, 194, 215, 223, 227, 228, 242, 247, 248], "product": [9, 191, 280], "among": [10, 193], "It": [10, 11, 19, 24, 27, 28, 30, 35, 39, 40, 43, 45, 46, 49, 66, 79, 82, 86, 89, 90, 92, 97, 98, 101, 103, 104, 106, 113, 119, 123, 131, 133, 135, 142, 152, 153, 159, 166, 178, 181, 193, 194, 196, 200, 210, 216, 222, 232, 233, 234, 238, 239, 240, 243, 245, 246, 248, 254, 258, 266, 267, 268, 269, 271, 272, 280, 283, 285], "analyz": [10, 11, 19, 142, 161, 193, 194, 222, 254], "coordin": [10, 193], "timestamp": [10, 32, 46, 82, 86, 88, 97, 101, 116, 127, 139, 181, 190, 193, 196, 216, 223, 225, 231, 237, 238, 241, 242, 260, 264, 276, 278, 280], "possibl": [10, 106, 193, 248], "relat": [10, 106, 119, 139, 147, 193, 237, 248, 282], "servic": [10, 15, 145, 193, 204, 274], "conserv": [10, 13, 193, 197], "tourism": [10, 193], "hospit": [10, 193], "sequenti": [11, 30, 39, 113, 120, 194, 214, 254, 256, 257, 258], "preserv": [11, 194], "order": [11, 54, 60, 73, 79, 80, 119, 142, 185, 194, 205, 211, 213, 223, 254, 255, 264], "instanc": [11, 119, 142, 194, 254], "transport": [11, 13, 147, 194, 197, 282], "urban": [11, 13, 15, 145, 147, 194, 197, 204, 274, 282], "plan": [11, 13, 15, 16, 145, 147, 194, 197, 204, 209, 274, 282], "alwai": [12, 195, 264], "entir": [12, 19, 195, 222, 280], "interest": [12, 78, 79, 80, 116, 195, 210, 260, 261], "In": [12, 24, 30, 39, 45, 75, 113, 116, 119, 121, 123, 127, 131, 135, 139, 145, 147, 149, 152, 153, 162, 195, 196, 208, 223, 237, 257, 261, 264, 270, 274, 277, 280, 282, 283, 286], "word": [12, 113, 195, 196, 223, 256, 258, 264], "agricultur": [12, 17, 195, 212], "crop": [12, 195], "public": [12, 54, 185, 195], "health": [12, 195], "surveil": [12, 195], "disast": [12, 17, 145, 195, 212, 274], "describ": [13, 197, 276], "consist": [13, 14, 17, 18, 143, 190, 197, 203, 212, 215, 263, 276, 280], "activ": [13, 120, 197], "area": [13, 197], "interv": [13, 18, 19, 28, 82, 136, 137, 138, 139, 140, 143, 197, 215, 216, 217, 218, 222, 224, 228, 235, 237, 247, 263], "reveal": [13, 197], "movement": [13, 197], "human": [13, 197], "logist": [13, 197], "infrastructur": [13, 197], "transact": [14, 24, 26, 27, 28, 29, 30, 31, 32, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 141, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 203, 205, 206, 207, 208, 210, 211, 213, 214, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 253, 254, 255, 256, 257, 258, 260, 261, 262, 263, 264, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "databas": [14, 16, 24, 26, 27, 28, 29, 30, 31, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 136, 138, 139, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 203, 205, 206, 207, 208, 209, 210, 211, 213, 214, 216, 220, 221, 223, 224, 225, 226, 227, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 263, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 280, 281, 283, 285], "contribut": [14, 16, 17, 141, 203, 209, 212, 253], "significantli": [14, 17, 141, 203, 212, 253], "reflect": [14, 15, 17, 203, 204, 212], "domain": [14, 15, 17, 203, 204, 212], "georeferenc": [15, 204], "combin": [15, 45, 46, 66, 86, 88, 92, 103, 104, 108, 148, 165, 181, 196, 200, 204, 226, 231, 234, 245, 246, 251, 284], "distribut": [15, 17, 30, 39, 49, 101, 176, 204, 212], "lb": [15, 204], "develop": [15, 145, 204, 274], "The": [16, 24, 26, 27, 29, 30, 31, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 136, 139, 140, 148, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 209, 210, 211, 213, 216, 217, 218, 220, 221, 224, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 284, 285], "hupm": [16, 20, 209, 219], "maxim": [16, 20, 44, 82, 87, 96, 137, 139, 161, 174, 209, 216, 217, 218, 233, 244], "from": [16, 24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 144, 145, 146, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 198, 200, 201, 202, 205, 206, 207, 208, 209, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 283, 285], "perspect": [16, 209], "diagnosi": [16, 209], "howev": [16, 24, 26, 27, 29, 31, 37, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 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164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "t": [24, 26, 27, 30, 31, 32, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 190, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "sourc": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 39, 40, 41, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "_correlatedpattern": [24, 152, 153], "descript": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 280, 281, 283, 285], "fundament": [24, 43, 45, 48, 49, 69, 84, 88, 91, 93, 97, 100, 101, 106, 113, 121, 123, 131, 133, 152, 153, 158, 159, 162, 163, 165, 166, 174, 178, 201, 220, 227, 229, 230, 231, 238, 239, 240, 241, 242, 244, 248, 256, 257, 258, 266, 267, 268, 269, 271, 272, 283, 285], "algorithm": [24, 26, 33, 43, 45, 46, 48, 49, 50, 52, 54, 60, 64, 66, 69, 71, 75, 76, 78, 79, 80, 82, 84, 86, 89, 90, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 198, 200, 201, 202, 206, 207, 208, 210, 211, 216, 217, 218, 220, 221, 225, 226, 227, 232, 233, 234, 236, 239, 240, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 278, 281, 283, 285], "correl": [24, 52, 95, 152, 153, 154, 182, 183, 190, 214, 235, 236, 264, 265], "fp": [24, 28, 43, 45, 49, 131, 152, 153, 159, 166, 178, 283], "growth": [24, 48, 49, 75, 82, 86, 90, 97, 100, 113, 127, 152, 153, 174, 178, 208, 216, 225, 233, 242, 244, 258, 278], "depth": [24, 46, 82, 89, 98, 113, 119, 152, 153, 181, 216, 217, 218, 232, 243, 256, 258], "first": [24, 45, 46, 49, 75, 80, 82, 86, 89, 98, 110, 113, 119, 152, 153, 162, 178, 181, 206, 213, 216, 217, 218, 223, 225, 232, 243, 252, 256, 257, 258, 264, 276], "search": [24, 43, 45, 46, 49, 54, 56, 58, 62, 75, 76, 82, 84, 89, 98, 113, 119, 121, 131, 133, 152, 153, 158, 159, 162, 166, 176, 177, 178, 181, 185, 188, 189, 192, 214, 216, 217, 218, 221, 232, 243, 256, 257, 258, 283, 285], "lee": [24, 97, 127, 152, 153, 239, 277], "y": [24, 32, 33, 43, 45, 71, 97, 104, 116, 117, 119, 120, 152, 153, 159, 166, 202, 238, 246, 261, 262], "kim": [24, 152, 153], "w": [24, 79, 116, 127, 152, 153, 211, 260, 277], "cao": [24, 152, 153], "d": [24, 152, 153, 255, 264, 265], "han": [24, 43, 45, 84, 113, 152, 153, 158, 159, 166, 220, 258], "j": [24, 43, 45, 46, 48, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 91, 97, 110, 113, 116, 119, 120, 123, 127, 131, 152, 153, 159, 166, 174, 181, 202, 205, 206, 211, 213, 216, 217, 218, 220, 225, 231, 232, 240, 252, 256, 257, 258, 260, 266, 277, 283], "2003": [24, 45, 152, 153, 164], "icdm": [24, 123, 152, 153, 270], "pp": [24, 45, 49, 56, 62, 69, 79, 80, 93, 97, 110, 116, 129, 131, 133, 152, 153, 162, 176, 188, 192, 201, 210, 213, 227, 242, 252, 260, 281, 283, 285], "581": [24, 152, 153], "584": [24, 152, 153], "paramet": [24, 26, 27, 28, 29, 31, 32, 33, 35, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 272, 275, 277, 278, 281, 283, 285], "name": [24, 26, 27, 28, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 281, 283, 285], "input": [24, 26, 27, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "file": [24, 26, 27, 28, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "complet": [24, 26, 28, 29, 30, 31, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 224, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 281, 283, 285], "ofil": [24, 26, 27, 28, 29, 30, 31, 32, 35, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "output": [24, 26, 27, 28, 29, 30, 31, 32, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "store": [24, 26, 27, 29, 30, 31, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "user": [24, 26, 27, 28, 29, 31, 37, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 139, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 254, 256, 257, 258, 260, 261, 262, 263, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "specifi": [24, 29, 32, 33, 37, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "either": [24, 29, 40, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 280, 281, 283, 285], "count": [24, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 110, 113, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "proport": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 224, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "size": [24, 29, 30, 32, 33, 39, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "If": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 190, 192, 198, 200, 201, 202, 205, 207, 210, 211, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 281, 283, 285], "program": [24, 26, 29, 30, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 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221, 225, 227, 229, 230, 231, 233, 236, 238, 239, 240, 241, 242, 244, 248, 251, 252, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "itemsetcount": [24, 46, 48, 90, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 135, 152, 153, 174, 181, 227, 233, 236, 238, 239, 240, 241, 242, 244, 248, 251, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 278], "finalpattern": [24, 26, 31, 43, 45, 46, 48, 49, 50, 64, 66, 69, 78, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 198, 200, 201, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "dict": [24, 26, 27, 30, 31, 33, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "itemsetbuff": [24, 54, 56, 58, 60, 62, 108, 152, 153, 185, 188, 189, 251], "maxpatternlength": [24, 108, 152, 153, 251], "constraint": [24, 73, 79, 101, 108, 110, 113, 116, 139, 143, 152, 153, 205, 211, 237, 251, 252, 256, 257, 258, 260, 261, 263], "length": [24, 27, 30, 32, 39, 40, 43, 75, 79, 82, 108, 113, 121, 123, 125, 127, 135, 152, 153, 158, 207, 210, 216, 217, 218, 251, 256, 257, 258, 266, 267, 268, 269, 270, 271, 272, 275, 278], "termin": [24, 26, 45, 46, 50, 56, 93, 97, 98, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 179, 181, 188, 227, 238, 239, 243, 266, 267, 268, 269, 270, 272, 275, 277, 278, 281, 283, 285], "command": [24, 26, 45, 46, 50, 56, 93, 97, 98, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 179, 181, 188, 227, 238, 239, 243, 266, 267, 268, 269, 270, 272, 275, 277, 278, 281, 283, 285], "format": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "venv": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 88, 89, 91, 93, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 227, 230, 231, 232, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 266, 267, 268, 269, 270, 272, 275, 277, 278, 281, 283, 285], "python3": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "py": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "inputfil": [24, 26, 27, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "outputfil": [24, 26, 27, 28, 30, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "exampl": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "sampletdb": [24, 26, 48, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 89, 90, 93, 95, 97, 98, 100, 101, 106, 110, 116, 117, 123, 125, 127, 135, 152, 153, 155, 156, 174, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 227, 232, 233, 236, 240, 241, 242, 243, 244, 248, 252, 260, 261, 262, 266, 271, 275, 277, 278], "txt": [24, 26, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "25": [24, 152, 153], "2": [24, 40, 48, 50, 52, 54, 56, 58, 60, 62, 69, 73, 79, 80, 88, 89, 91, 97, 98, 100, 106, 108, 113, 116, 121, 127, 129, 152, 153, 174, 179, 183, 185, 188, 189, 190, 192, 196, 201, 205, 211, 213, 223, 229, 230, 232, 240, 241, 242, 243, 244, 248, 251, 256, 258, 260, 264, 265, 276, 277, 278, 280, 281], "call": [24, 26, 45, 46, 50, 56, 58, 78, 80, 82, 97, 98, 113, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 179, 181, 188, 189, 218, 238, 239, 243, 256, 257, 266, 267, 268, 269, 270, 275, 276, 277, 278, 281, 283, 285], "alg": [24, 26, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "obj": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "getpattern": [24, 26, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "print": [24, 26, 28, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "number": [24, 26, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 280, 281, 283, 285], "len": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "savepattern": [24, 45, 46, 48, 75, 76, 84, 101, 104, 106, 110, 113, 117, 120, 125, 127, 131, 152, 153, 164, 166, 174, 181, 221, 246, 248, 252, 256, 257, 258, 262, 275, 278, 283], "df": [24, 26, 28, 43, 45, 46, 48, 49, 50, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "getpatternsasdatafram": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "memuss": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "getmemoryuss": [24, 26, 28, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 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227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "after": [24, 26, 32, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "final": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 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270, 271, 272, 275, 277, 278, 281, 283, 285], "none": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 39, 40, 43, 45, 52, 54, 56, 62, 71, 75, 79, 80, 82, 84, 88, 95, 97, 100, 101, 108, 110, 117, 119, 120, 123, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 183, 185, 188, 192, 202, 206, 208, 210, 211, 213, 216, 217, 218, 220, 221, 229, 230, 231, 236, 238, 239, 240, 241, 242, 244, 251, 252, 262, 266, 267, 268, 269, 277, 281, 283, 285], "main": [24, 26, 31, 43, 45, 52, 73, 75, 79, 80, 84, 86, 88, 90, 91, 92, 97, 100, 103, 104, 108, 113, 120, 123, 125, 127, 131, 148, 152, 153, 155, 159, 166, 183, 205, 207, 210, 211, 213, 220, 221, 226, 229, 230, 231, 233, 234, 240, 244, 245, 246, 251, 257, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 283, 284], "method": [24, 26, 27, 30, 31, 32, 33, 37, 39, 40, 43, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 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\ No newline at end of file
+Search.setIndex({"docnames": ["ContiguousFrequentPatterns1", "CorrelatedPatternMining1", "CoveragePatternMining1", "FaultTolerantPatternMining1", "FrequentPatternWithMultipleMinimumSupport1", "FuzzyCorrelatedPatternMining1", "FuzzyFrequentPatternMining1", "FuzzyGeoReferencedFrequentPatternMining1", "FuzzyGeoReferencedPeriodicFrequentPatternMining1", "FuzzyPeriodicFrequentPatternMining1", "GeoReferencedFrequentPatternMining1", "GeoReferencedFrequentSequencePatternMining1", "GeoReferencedPartialPeriodicPatternMining1", "GeoReferencedPeriodicFrequentPatternMining1", "HighUtilityFrequentPatternMining1", "HighUtilityGeo-referencedFrequentPatternMining1", "HighUtilityPatternMining1", "HighUtilitySpatialPatternMining1", "LocalPeriodicPatternMining1", "MultiplePartialPeriodicPatternMining1", "PAMI", "PAMI.AssociationRules", "PAMI.AssociationRules.basic", "PAMI.correlatedPattern", "PAMI.correlatedPattern.basic", "PAMI.coveragePattern", "PAMI.coveragePattern.basic", "PAMI.extras", 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"UncertainPeriodicFrequentPatternMining1.rst", "WeightedFrequentNeighbourhoodPatternMining1.rst", "WeightedFrequentPatternMining1.rst", "WeightedFrequentRegularPatternMining1.rst", "contiguousFrequentPatterns.rst", "contiguousPatternMining.rst", "correlatedPatternBasicCoMine.rst", "correlatedPatternBasicCoMinePlus.rst", "correlatedPatternMining.rst", "coveragePatternBasicCMine.rst", "coveragePatternBasicCPPG.rst", "coveragePatternMining.rst", "faultTolerantFrequentPatternBasicFTApriori.rst", "faultTolerantFrequentPatternBasicFTFPGrowth.rst", "faultTolerantPatternMining.rst", "frequent1.rst", "frequentPatternBasicApriori.rst", "frequentPatternBasicECLAT.rst", "frequentPatternBasicECLATDiffset.rst", "frequentPatternBasicECLATbitset.rst", "frequentPatternBasicFPGrowth.rst", "frequentPatternCUDAcuApriori.rst", "frequentPatternCUDAcuAprioriBit.rst", "frequentPatternCUDAcuAprioriGCT.rst", "frequentPatternCUDAcuAprioriTID.rst", "frequentPatternCUDAcuECLAT.rst", "frequentPatternCUDAcuECLATBit.rst", "frequentPatternCUDAcuECLATGCT.rst", "frequentPatternMaximalmaxFPGrowth.rst", "frequentPatternMining.rst", "frequentPatternPysparkParallelApriori.rst", "frequentPatternPysparkParallelECLAT.rst", "frequentPatternPysparkParallelFPGrowth.rst", "frequentPatternTopkFAE.rst", "frequentPatternWithMultipleMinimumSupport.rst", "frequentPatternclosedCHARM.rst", "fuzzyCorrelatedPatternMining.rst", "fuzzyCorrelatedPatternbasicFCPGrowth.rst", "fuzzyFrequentPatternMining.rst", "fuzzyFrequentPatternbasicFFIMiner.rst", "fuzzyGeoReferencedFrequentPatternMining.rst", "fuzzyGeoReferencedPeriodicFrequentPatternMining.rst", "fuzzyGeoreferencedFrequentPatternbasicFFSPMiner.rst", "fuzzyGeoreferencedPeriodicFrequentPatternbasicFGPFPMiner.rst", "fuzzyPatternMining.rst", "fuzzyPeriodicFrequentPatternMining.rst", "fuzzyPeriodicFrequentPatternbasicFPFPMiner.rst", "geoReferencedFrequentPatternMining.rst", "geoReferencedFrequentSequencePatternMining.rst", "geoReferencedPartialPeriodicPatternMining.rst", "geoReferencedPatternMining.rst", "geoReferencedPeriodicFrequentPatternMining.rst", "geoReferencedPeriodicFrequentPatternbasicGPFPMiner.rst", "georeferencedFrequentPatternbasicFSPGrowth.rst", "georeferencedFrequentPatternbasicSpatialECLAT.rst", "georeferencedPartialPeriodicPatternbasicSTEclat.rst", "highUtilityFrequentPatternBasicHUFIM.rst", "highUtilityFrequentPatternMining.rst", "highUtilityGeo-referencedFrequentPatternMining.rst", "highUtilityGeoreferencedFrequentPatternBasicSHUFIM.rst", "highUtilityPatternBasicEFIM.rst", "highUtilityPatternBasicHMiner.rst", "highUtilityPatternBasicUPGrowth.rst", "highUtilityPatternMining.rst", "highUtilitySpatialPatternBasicHDSHUIM.rst", "highUtilitySpatialPatternBasicSHUIM.rst", "highUtilitySpatialPatternMining.rst", "highUtilitySpatialPatternTopkTKSHUIM.rst", "index.rst", "localPeriodicPatternMining.rst", "localPeriodicPatternbasicLPPGrowth.rst", "localPeriodicPatternbasicLPPMBreadth.rst", "localPeriodicPatternbasicLPPMDepth.rst", "modules.rst", "multipleMinimumSupportBasedFrequentPatternBasicCFPGrowth.rst", "multipleMinimumSupportBasedFrequentPatternBasicCFPGrowthPlus.rst", "multiplePartialPeriodicPatternMining.rst", "multipleTimeseriesPatternMining.rst", "partialPeriodicFrequentPatternMining.rst", "partialPeriodicFrequentPatternbasicGPFgrowth.rst", "partialPeriodicFrequentPatternbasicPPF_DFS.rst", "partialPeriodicPatternInMultipleTimeSeriesPPGrowth.rst", "partialPeriodicPatternMining.rst", "partialPeriodicPatternbasicGThreePGrowth.rst", "partialPeriodicPatternbasicPPPGrowth.rst", "partialPeriodicPatternbasicPPP_ECLAT.rst", "partialPeriodicPatternclosedPPPClose.rst", "partialPeriodicPatternmaximalMax3PGrowth.rst", "partialPeriodicPatterntopkk3PMiner.rst", "periodicCorrelatedPatternMining.rst", "periodicCorrelatedPatternbasicEPCPGrowth.rst", "periodicFrequentPatternMining.rst", "periodicFrequentPatternbasicPFECLAT.rst", "periodicFrequentPatternbasicPFPGrowth.rst", "periodicFrequentPatternbasicPFPGrowthPlus.rst", "periodicFrequentPatternbasicPFPMC.rst", "periodicFrequentPatternbasicPSGrowth.rst", "periodicFrequentPatternclosedCPFPMiner.rst", "periodicFrequentPatternmaximalMaxPFGrowth.rst", "periodicFrequentPatterntopkTopkPFPTopkPFP.rst", "periodicFrequentPatterntopkkPFPMinerkPFPMiner.rst", "recurringPatternMining.rst", "recurringPatternbasicRPGrowth.rst", "relativeFrequent.rst", "relativeFrequentPattern.rst", "relativeFrequentPatternBasicRSFPGrowth.rst", "relativeHighUtilityPatternBasicRHUIM.rst", "relativeHighUtilityPatternMining.rst", "sequentialFrequentPatternMining.rst", "sequentialPatternMining.rst", "sequentialPatternMiningBasicSPADE.rst", "sequentialPatternMiningBasicSPAM.rst", "sequentialPatternMiningBasicprefixSpan.rst", "sequentialPatternMiningClosedbide.rst", "stablePeriodicFrequentPatternbasicSPPEclat.rst", "stablePeriodicFrequentPatternbasicSPPGrowth.rst", "stablePeriodicFrequentPatterntopKTSPIN.rst", "stablePeriodicPatternMining.rst", "temporalPatternMining.rst", "transactionalPatternMining.rst", "uncertainFrequentPatternBasicCUFPTree.rst", "uncertainFrequentPatternBasicPUFGrowth.rst", "uncertainFrequentPatternBasicTUFP.rst", "uncertainFrequentPatternBasicTubeP.rst", "uncertainFrequentPatternBasicTubeS.rst", "uncertainFrequentPatternBasicUFGrowth.rst", "uncertainFrequentPatternBasicUVECLAT.rst", "uncertainFrequentPatternMining.rst", "uncertainGeoReferencedFrequentPatternMining.rst", "uncertainGeoreferencedFrequentPatternBasicGFPGrowth.rst", "uncertainPatternMining.rst", "uncertainPeriodicFrequentPatternBasicUPFPGrowth.rst", "uncertainPeriodicFrequentPatternBasicUPFPGrowthPlus.rst", "uncertainPeriodicFrequentPatternMining.rst", "utilityPatternMining.rst", "weightedFrequentNeighbourhoodPatternBasicSWFPGrowth.rst", "weightedFrequentNeighbourhoodPatternMining.rst", "weightedFrequentPatternBasicWFIM.rst", "weightedFrequentPatternMining.rst", "weightedFrequentRegularPatternBasicWFRIMiner.rst", "weightedFrequentRegularPatternMining.rst"], "titles": ["Contiguous Frequent Patterns", "Correlated Pattern Mining", "Coverage Pattern Mining", "Fault-Tolerant Frequent Pattern Mining", "Frequent pattern With Multiple Minimum Support", "Fuzzy Correlated Pattern Mining", "Fuzzy Frequent Pattern Mining", "Fuzzy Geo-referenced Frequent Pattern Mining", "Fuzzy Geo-referenced Periodic Frequent Pattern Mining", "Fuzzy Periodic Frequent Pattern Mining", "Geo-referenced Frequent Pattern Mining", "Geo-referenced Frequent Sequence Pattern mining", "Geo-referenced Partial Periodic Pattern Mining", "Geo-referenced Periodic Frequent Pattern Mining", "High-Utility Frequent Pattern Mining", "High-Utility Geo-referenced Frequent Pattern Mining", "High-Utility Pattern mining", "High-Utility Spatial Pattern Mining", "Local Periodic Pattern Mining", "Multiple Partial Periodic Pattern Mining", "PAMI package", "PAMI.AssociationRules package", "PAMI.AssociationRules.basic package", "PAMI.correlatedPattern package", "PAMI.correlatedPattern.basic package", "PAMI.coveragePattern package", "PAMI.coveragePattern.basic package", "PAMI.extras package", "PAMI.extras.DF2DB package", "PAMI.extras.calculateMISValues package", "PAMI.extras.dbStats package", "PAMI.extras.fuzzyTransformation package", "PAMI.extras.generateDatabase package", "PAMI.extras.graph package", "PAMI.extras.image2Database package", "PAMI.extras.imageProcessing package", "PAMI.extras.messaging package", "PAMI.extras.neighbours package", "PAMI.extras.sampleDatasets package", "PAMI.extras.stats package", "PAMI.extras.syntheticDataGenerator package", "PAMI.extras.visualize package", "PAMI.faultTolerantFrequentPattern package", "PAMI.faultTolerantFrequentPattern.basic package", "PAMI.frequentPattern package", "PAMI.frequentPattern.basic package", "PAMI.frequentPattern.closed package", "PAMI.frequentPattern.cuda package", "PAMI.frequentPattern.maximal package", "PAMI.frequentPattern.pyspark package", "PAMI.frequentPattern.topk package", "PAMI.fuzzyCorrelatedPattern package", "PAMI.fuzzyCorrelatedPattern.basic package", "PAMI.fuzzyFrequentPattern package", "PAMI.fuzzyFrequentPattern.basic package", "PAMI.fuzzyGeoreferencedFrequentPattern package", "PAMI.fuzzyGeoreferencedFrequentPattern.basic package", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern package", "PAMI.fuzzyGeoreferencedPeriodicFrequentPattern.basic package", "PAMI.fuzzyPartialPeriodicPatterns package", "PAMI.fuzzyPartialPeriodicPatterns.basic package", "PAMI.fuzzyPeriodicFrequentPattern package", "PAMI.fuzzyPeriodicFrequentPattern.basic package", "PAMI.geoReferencedPeriodicFrequentPattern package", "PAMI.geoReferencedPeriodicFrequentPattern.basic package", "PAMI.georeferencedFrequentPattern package", "PAMI.georeferencedFrequentPattern.basic package", "PAMI.georeferencedFrequentSequencePattern package", "PAMI.georeferencedPartialPeriodicPattern package", "PAMI.georeferencedPartialPeriodicPattern.basic package", "PAMI.highUtilityFrequentPattern package", "PAMI.highUtilityFrequentPattern.basic package", "PAMI.highUtilityGeoreferencedFrequentPattern package", "PAMI.highUtilityGeoreferencedFrequentPattern.basic package", "PAMI.highUtilityPattern package", "PAMI.highUtilityPattern.basic package", "PAMI.highUtilityPattern.parallel package", "PAMI.highUtilityPatternsInStreams package", "PAMI.highUtilitySpatialPattern package", "PAMI.highUtilitySpatialPattern.basic package", "PAMI.highUtilitySpatialPattern.topk package", "PAMI.localPeriodicPattern package", "PAMI.localPeriodicPattern.basic package", "PAMI.multipleMinimumSupportBasedFrequentPattern package", "PAMI.multipleMinimumSupportBasedFrequentPattern.basic package", "PAMI.partialPeriodicFrequentPattern package", "PAMI.partialPeriodicFrequentPattern.basic package", "PAMI.partialPeriodicPattern package", "PAMI.partialPeriodicPattern.basic package", "PAMI.partialPeriodicPattern.closed package", "PAMI.partialPeriodicPattern.maximal package", "PAMI.partialPeriodicPattern.pyspark package", "PAMI.partialPeriodicPattern.topk package", "PAMI.partialPeriodicPatternInMultipleTimeSeries package", "PAMI.periodicCorrelatedPattern package", "PAMI.periodicCorrelatedPattern.basic package", "PAMI.periodicFrequentPattern package", "PAMI.periodicFrequentPattern.basic package", "PAMI.periodicFrequentPattern.closed package", "PAMI.periodicFrequentPattern.cuda package", "PAMI.periodicFrequentPattern.maximal package", "PAMI.periodicFrequentPattern.pyspark package", "PAMI.periodicFrequentPattern.topk package", "PAMI.periodicFrequentPattern.topk.TopkPFP package", "PAMI.periodicFrequentPattern.topk.kPFPMiner package", "PAMI.recurringPattern package", "PAMI.recurringPattern.basic package", "PAMI.relativeFrequentPattern package", "PAMI.relativeFrequentPattern.basic package", "PAMI.relativeHighUtilityPattern package", "PAMI.relativeHighUtilityPattern.basic package", "PAMI.sequence package", "PAMI.sequentialPatternMining package", "PAMI.sequentialPatternMining.basic package", "PAMI.sequentialPatternMining.closed package", "PAMI.stablePeriodicFrequentPattern package", "PAMI.stablePeriodicFrequentPattern.basic package", "PAMI.stablePeriodicFrequentPattern.topK package", "PAMI.subgraphMining package", "PAMI.subgraphMining.basic package", "PAMI.subgraphMining.topK package", "PAMI.uncertainFaultTolerantFrequentPattern package", "PAMI.uncertainFrequentPattern package", "PAMI.uncertainFrequentPattern.basic package", "PAMI.uncertainGeoreferencedFrequentPattern package", "PAMI.uncertainGeoreferencedFrequentPattern.basic package", "PAMI.uncertainPeriodicFrequentPattern package", "PAMI.uncertainPeriodicFrequentPattern.basic package", "PAMI.weightedFrequentNeighbourhoodPattern package", "PAMI.weightedFrequentNeighbourhoodPattern.basic package", "PAMI.weightedFrequentPattern package", "PAMI.weightedFrequentPattern.basic package", "PAMI.weightedFrequentRegularPattern package", "PAMI.weightedFrequentRegularPattern.basic package", "PAMI.weightedUncertainFrequentPattern package", "PAMI.weightedUncertainFrequentPattern.basic package", "Partial Periodic Frequent Pattern Mining", "Partial Periodic Pattern Mining", "Periodic correlated pattern mining", "Periodic Frequent Pattern Mining", "Recurring Pattern Mining", "Relative High-Utility Pattern Mining", "Sequential Frequent Pattern mining", "Stable Periodic Pattern Mining", "Uncertain Frequent Pattern mining", "Uncertain Geo-Referenced Frequent Pattern mining", "Uncertain Periodic Frequent Pattern mining", "Weighted Frequent Neighbourhood Pattern Mining", "Weighted Frequent Pattern Mining", "Weighted Frequent Regular Pattern Mining", "<no title>", "Contiguous Patterns", "CoMine", "CoMinePlus", "Basic", "CMine", "CPPG", "Basic", "FTApriori", "FTFPGrowth", "Basic", "Frequent Pattern mining", "Apriori", "ECLAT", "ECLATDiffset", "ECLATbitset", "FPGrowth", "cuApriori", "cuAprioriBit", "cudaAprioriGCT", 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138, 139, 140, 141, 142, 143, 144, 145, 146, 149, 152, 153, 154, 157, 158, 159, 160, 162, 163, 164, 165, 166, 174, 176, 177, 178, 180, 181, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 200, 201, 202, 205, 207, 208, 210, 211, 213, 216, 217, 218, 222, 223, 227, 229, 230, 231, 232, 233, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 246, 247, 248, 252, 253, 254, 256, 257, 258, 260, 261, 262, 263, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 277, 278, 279, 280, 281, 283, 285, 286], "applic": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 79, 116, 121, 123, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 154, 157, 160, 161, 180, 182, 184, 186, 187, 191, 193, 194, 195, 197, 203, 204, 209, 210, 212, 215, 222, 224, 228, 235, 237, 247, 249, 250, 253, 254, 260, 263, 266, 273, 274, 279, 280, 282, 284, 286], "fraud": [1, 14, 154, 203], "detect": [1, 14, 18, 24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 82, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 137, 140, 152, 153, 154, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 203, 205, 207, 210, 211, 215, 216, 217, 218, 227, 228, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 247, 248, 249, 250, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "suppli": [1, 154, 249, 250], "chain": [1, 154, 249, 250], "manag": [1, 12, 13, 17, 18, 136, 145, 154, 195, 197, 212, 215, 224, 274], "healthcar": [1, 2, 4, 5, 7, 14, 19, 137, 138, 139, 142, 144, 146, 148, 149, 154, 157, 180, 182, 186, 203, 222, 228, 235, 237, 254, 273, 279, 284, 286], "analysi": [1, 2, 3, 4, 5, 6, 8, 9, 14, 19, 50, 137, 138, 139, 141, 143, 148, 149, 154, 157, 160, 179, 180, 182, 184, 187, 191, 203, 222, 228, 235, 237, 249, 250, 253, 263, 284, 286], "retail": [1, 2, 4, 7, 138, 139, 141, 149, 154, 157, 180, 186, 235, 237, 253, 286], "market": [1, 4, 5, 7, 14, 19, 141, 142, 143, 148, 154, 180, 182, 186, 203, 222, 249, 250, 253, 254, 263, 284], "basic": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 23, 25, 28, 42, 44, 48, 51, 53, 55, 57, 59, 61, 63, 65, 68, 70, 72, 74, 78, 81, 83, 85, 87, 89, 91, 93, 94, 96, 98, 100, 101, 105, 107, 109, 112, 115, 117, 118, 121, 122, 124, 126, 128, 130, 132, 134, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 152, 153, 155, 156, 158, 159, 161, 162, 163, 164, 165, 166, 174, 183, 185, 188, 189, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 236, 238, 239, 240, 241, 242, 243, 244, 248, 249, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "techniqu": [2, 3, 11, 12, 19, 24, 45, 46, 54, 56, 58, 62, 84, 113, 137, 142, 152, 153, 157, 160, 162, 181, 185, 188, 189, 192, 194, 195, 221, 222, 228, 254, 256, 257, 258], "focus": [2, 11, 12, 19, 119, 138, 139, 142, 143, 157, 194, 195, 222, 235, 237, 254, 263], "identifi": [2, 7, 12, 19, 119, 139, 142, 143, 157, 161, 186, 190, 195, 222, 237, 254, 255, 263, 265, 276, 280], "cover": [2, 12, 19, 157, 195, 222], "substanti": [2, 157], "portion": [2, 157], "irrespect": [2, 157], "frequenc": [2, 5, 24, 30, 39, 43, 45, 46, 48, 84, 86, 88, 90, 91, 93, 95, 97, 100, 101, 106, 108, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 147, 149, 152, 153, 157, 158, 159, 165, 166, 174, 181, 182, 220, 221, 224, 226, 227, 229, 230, 231, 233, 236, 238, 239, 240, 241, 242, 244, 248, 249, 250, 251, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 282, 283, 285, 286], "unlik": [2, 3, 4, 6, 18, 136, 137, 138, 139, 143, 144, 146, 157, 160, 180, 184, 215, 224, 228, 235, 237, 263, 273, 279], "tradit": [2, 3, 4, 6, 18, 24, 52, 137, 138, 139, 143, 144, 146, 152, 153, 157, 160, 180, 183, 184, 215, 228, 235, 237, 263, 273, 279], "frequent": [2, 12, 17, 26, 28, 29, 31, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 143, 150, 151, 156, 157, 158, 159, 160, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 200, 201, 202, 203, 204, 205, 206, 207, 208, 210, 211, 212, 213, 214, 216, 217, 218, 220, 221, 224, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 254, 255, 256, 257, 258, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286], "which": [2, 3, 4, 6, 14, 18, 26, 27, 54, 56, 58, 62, 64, 66, 71, 75, 82, 86, 88, 97, 98, 100, 101, 103, 108, 110, 113, 116, 119, 120, 123, 136, 138, 139, 144, 146, 148, 155, 156, 157, 160, 180, 184, 185, 188, 189, 192, 198, 200, 202, 203, 206, 215, 216, 217, 218, 224, 225, 226, 231, 235, 237, 238, 239, 240, 241, 242, 243, 244, 245, 251, 252, 256, 258, 260, 270, 273, 279, 284], "priorit": [2, 157], "high": [2, 48, 52, 54, 56, 62, 71, 73, 75, 76, 79, 80, 110, 148, 157, 174, 183, 190, 192, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 252, 253, 280, 284], "emphas": [2, 157], "have": [2, 18, 49, 75, 79, 80, 82, 86, 113, 116, 119, 144, 146, 148, 157, 178, 190, 206, 210, 211, 213, 215, 216, 217, 218, 225, 249, 250, 255, 256, 257, 258, 260, 261, 264, 273, 276, 279, 280, 284], "wide": [2, 157], "across": [2, 18, 157, 215], "consid": [2, 4, 5, 8, 18, 26, 40, 43, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 84, 97, 98, 100, 101, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 138, 139, 156, 157, 158, 159, 174, 176, 177, 178, 179, 180, 182, 183, 185, 187, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 215, 220, 221, 235, 237, 238, 239, 240, 241, 242, 243, 244, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 271, 275, 277, 278, 281, 283, 285], "signific": [2, 4, 17, 40, 147, 148, 149, 157, 180, 212, 282, 284, 286], "thei": [2, 119, 157], "overal": [2, 14, 157, 203], "characterist": [2, 4, 157, 180], "trend": [2, 13, 116, 139, 157, 197, 237, 261], "present": [2, 142, 157, 249, 250, 254], "understand": [2, 157], "broad": [2, 157], "inform": [2, 3, 6, 11, 24, 26, 43, 45, 46, 48, 82, 84, 86, 88, 90, 91, 93, 95, 97, 100, 101, 103, 106, 108, 116, 117, 119, 120, 123, 125, 127, 129, 131, 133, 135, 152, 153, 156, 157, 159, 160, 166, 174, 181, 184, 194, 216, 217, 218, 220, 221, 226, 227, 229, 230, 231, 233, 236, 238, 239, 240, 241, 242, 244, 245, 248, 251, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "decis": [2, 16, 157, 209], "make": [2, 6, 16, 113, 137, 143, 157, 184, 209, 228, 256, 257, 258, 263], "process": [2, 4, 7, 9, 10, 24, 26, 31, 35, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 142, 143, 149, 152, 153, 155, 156, 157, 158, 159, 161, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 185, 186, 188, 189, 191, 192, 193, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 254, 256, 257, 258, 260, 261, 262, 263, 265, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285, 286], "optim": [2, 4, 142, 143, 149, 157, 180, 254, 263, 286], "oper": [2, 43, 45, 75, 79, 84, 108, 119, 131, 157, 159, 166, 207, 210, 211, 220, 221, 251, 283], "improv": [2, 97, 157, 240], "effici": [2, 24, 26, 46, 54, 56, 58, 62, 66, 71, 75, 76, 97, 108, 113, 116, 121, 127, 135, 152, 153, 155, 157, 181, 185, 188, 189, 192, 200, 202, 206, 208, 238, 240, 242, 251, 256, 261, 278], "effect": [2, 43, 45, 49, 97, 113, 121, 131, 133, 157, 158, 159, 162, 166, 176, 177, 178, 190, 240, 256, 257, 258, 276, 280, 283, 285], "web": [2, 14, 138, 142, 157, 203, 235, 249, 250, 254], "usag": [2, 14, 24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 97, 100, 101, 106, 108, 110, 113, 116, 120, 121, 123, 125, 127, 129, 131, 133, 135, 138, 152, 153, 155, 156, 157, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 198, 200, 201, 202, 203, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 235, 238, 239, 241, 244, 248, 249, 250, 251, 252, 256, 257, 258, 260, 261, 266, 267, 268, 269, 270, 272, 275, 276, 277, 278, 280, 281, 283, 285], "manufactur": [2, 4, 6, 9, 143, 149, 157, 180, 184, 191, 249, 250, 263, 286], "social": [2, 157], "network": [2, 4, 9, 49, 137, 139, 148, 157, 176, 180, 191, 228, 237, 249, 250, 284], "approach": [3, 4, 5, 43, 45, 88, 91, 97, 113, 121, 123, 143, 159, 160, 166, 180, 182, 229, 230, 231, 238, 240, 241, 258, 263, 266], "aim": [3, 12, 16, 26, 73, 79, 80, 116, 138, 143, 155, 160, 195, 205, 209, 211, 213, 235, 260, 261, 263], "discov": [3, 7, 10, 11, 12, 14, 16, 24, 26, 43, 45, 46, 48, 49, 50, 52, 56, 60, 62, 66, 69, 73, 75, 76, 78, 79, 80, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 138, 139, 140, 143, 152, 153, 155, 156, 158, 159, 160, 162, 163, 165, 166, 174, 176, 177, 178, 179, 181, 183, 186, 188, 192, 193, 194, 195, 200, 201, 203, 205, 209, 210, 211, 213, 220, 225, 227, 229, 230, 231, 232, 233, 234, 235, 236, 237, 239, 240, 242, 243, 244, 245, 246, 247, 248, 252, 256, 257, 258, 260, 262, 263, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "larg": [3, 45, 56, 66, 79, 80, 90, 97, 98, 100, 104, 110, 160, 161, 162, 188, 200, 210, 213, 233, 240, 243, 244, 246, 252], "contain": [3, 10, 33, 71, 73, 75, 76, 79, 80, 110, 119, 144, 145, 146, 160, 193, 196, 202, 205, 206, 211, 213, 223, 252, 264, 265, 273, 274, 279, 280], "both": [3, 12, 80, 113, 138, 139, 160, 195, 213, 235, 237, 256], "uncertain": [3, 6, 40, 84, 121, 123, 125, 127, 135, 160, 184, 214, 220, 221, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 277, 278, 279], "record": [3, 24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 139, 152, 153, 155, 156, 158, 159, 160, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 220, 221, 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "reli": [3, 5, 160, 182], "exact": [3, 6, 160, 184], "match": [3, 6, 32, 40, 160, 184], "base": [3, 4, 7, 10, 15, 24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 39, 40, 41, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 145, 147, 148, 149, 152, 153, 155, 156, 158, 159, 160, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 185, 186, 188, 189, 192, 193, 198, 200, 201, 202, 204, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 274, 275, 277, 278, 281, 282, 283, 284, 285, 286], "support": [3, 16, 24, 29, 45, 46, 49, 52, 54, 56, 58, 60, 62, 71, 73, 78, 84, 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279], "refer": [4, 7, 9, 24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 140, 145, 147, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 185, 186, 188, 189, 191, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 274, 275, 277, 278, 281, 282, 283, 285], "occur": [4, 7, 11, 12, 13, 14, 15, 17, 19, 137, 139, 140, 142, 147, 148, 149, 161, 180, 186, 194, 195, 197, 203, 204, 212, 222, 228, 237, 247, 254, 264, 282, 284, 286], "meet": [4, 24, 152, 153, 180], "threshold": [4, 24, 27, 28, 29, 35, 75, 76, 79, 80, 84, 103, 110, 119, 123, 125, 127, 129, 131, 135, 152, 153, 180, 210, 211, 213, 220, 221, 245, 252, 266, 275, 277, 278, 281, 283], "mine": [4, 20, 24, 26, 29, 31, 37, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 151, 152, 153, 155, 156, 157, 158, 159, 160, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 192, 193, 194, 195, 198, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 216, 217, 218, 220, 221, 222, 223, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 281, 282, 283, 284, 285, 286], "us": [4, 14, 15, 24, 26, 27, 29, 30, 31, 32, 33, 35, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 137, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 185, 188, 189, 190, 192, 198, 200, 201, 202, 203, 204, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "singl": [4, 45, 71, 75, 80, 110, 119, 120, 165, 180, 202, 206, 213, 252], "uniform": [4, 180, 264], "all": [4, 24, 26, 28, 30, 35, 39, 49, 54, 56, 58, 60, 62, 71, 73, 75, 78, 79, 80, 82, 84, 86, 89, 90, 91, 92, 106, 108, 110, 116, 119, 127, 152, 153, 155, 176, 178, 180, 185, 188, 189, 190, 192, 202, 205, 206, 207, 210, 211, 213, 216, 220, 221, 225, 226, 232, 233, 248, 249, 250, 251, 252, 260, 261, 264, 265, 276, 278], "vari": [4, 18, 136, 143, 145, 180, 215, 224, 263, 274, 280], "level": [4, 33, 101, 180], "By": [4, 180], "more": [4, 18, 66, 113, 143, 180, 200, 215, 256, 257, 258, 263, 264], "nuanc": [4, 180], "each": [4, 12, 14, 17, 19, 30, 39, 49, 73, 75, 79, 80, 82, 86, 113, 119, 139, 141, 145, 146, 176, 177, 178, 180, 190, 195, 203, 205, 208, 210, 211, 212, 213, 216, 217, 218, 222, 225, 226, 237, 249, 250, 253, 255, 256, 257, 264, 265, 274, 276, 279, 280], "evalu": [4, 180], "individu": [4, 180, 190, 276, 280], "its": [4, 17, 29, 30, 39, 54, 56, 58, 62, 82, 86, 113, 119, 136, 147, 149, 180, 185, 188, 189, 192, 212, 216, 217, 218, 224, 225, 257, 265, 280, 282, 286], "import": [4, 14, 15, 17, 24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 180, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 203, 204, 205, 206, 207, 208, 210, 211, 212, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 264, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "context": [4, 14, 15, 17, 139, 180, 203, 204, 212, 237], "traffic": [4, 8, 9, 19, 136, 137, 139, 143, 148, 180, 187, 191, 222, 224, 228, 237, 263, 284], "involv": [5, 7, 8, 9, 10, 11, 14, 15, 17, 19, 79, 137, 139, 141, 142, 144, 145, 146, 147, 148, 149, 182, 186, 187, 191, 193, 194, 203, 204, 210, 212, 222, 228, 237, 253, 254, 273, 274, 279, 282, 284, 286], "explor": [5, 71, 110, 113, 119, 182, 202, 252, 257], "itemset": [5, 24, 45, 46, 48, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 86, 88, 91, 101, 110, 123, 129, 131, 133, 135, 141, 149, 152, 153, 165, 174, 181, 182, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 226, 229, 230, 252, 253, 255, 270, 272, 281, 283, 285, 286], "exhibit": [5, 7, 8, 9, 12, 136, 137, 138, 139, 143, 147, 149, 182, 186, 187, 191, 195, 224, 228, 235, 237, 263, 282, 286], "linear": [5, 182], "assess": [5, 182], "through": [5, 119, 123, 182, 270], "instead": [5, 182], "sole": [5, 138, 182, 235], "co": [5, 182], "strength": [5, 182], "uncov": [5, 182], "basket": [5, 14, 91, 101, 141, 148, 182, 203, 249, 250, 253, 284], "analyt": [5, 14, 104, 148, 149, 182, 203, 246, 284, 286], "financi": [5, 6, 9, 137, 140, 141, 143, 146, 182, 184, 191, 228, 247, 253, 263, 279], "ffp": [6, 184], "captur": [6, 8, 136, 184, 187, 224], "inher": [6, 184], "partial": [6, 60, 69, 86, 88, 89, 90, 91, 92, 101, 184, 195, 196, 201, 214, 222, 223, 224, 225, 226, 228, 229, 230, 231, 232, 233, 234, 264], "event": [6, 8, 9, 10, 11, 12, 13, 15, 17, 19, 82, 136, 139, 142, 145, 147, 184, 187, 191, 193, 194, 195, 197, 204, 212, 216, 217, 218, 222, 223, 224, 237, 254, 274, 282], "requir": [6, 40, 73, 75, 136, 184, 205, 208, 224], "variat": [6, 12, 137, 184, 195, 228], "degre": [6, 136, 137, 184, 224, 228], "membership": [6, 54, 184, 185], "similar": [6, 184, 196], "them": [6, 113, 119, 137, 143, 184, 228, 257, 263], "suitabl": [6, 143, 184, 263], "imprecis": [6, 8, 9, 184, 187, 191], "medic": [6, 16, 184, 209], "qualiti": [6, 184], "control": [6, 26, 82, 86, 97, 98, 100, 101, 103, 108, 155, 156, 184, 216, 217, 218, 225, 226, 238, 239, 240, 241, 242, 243, 244, 245, 251], "geograph": [7, 8, 10, 11, 13, 145, 186, 187, 193, 194, 197, 274], "mai": [7, 9, 12, 13, 18, 19, 120, 136, 137, 143, 145, 146, 186, 191, 195, 197, 215, 222, 224, 228, 263, 264, 274, 279], "object": [7, 27, 28, 29, 30, 32, 33, 35, 36, 37, 39, 40, 41, 49, 52, 80, 82, 86, 91, 97, 101, 116, 119, 120, 147, 178, 183, 186, 190, 213, 216, 225, 242, 261, 276, 280, 282], "epidemiolog": [7, 8, 186, 187], "environment": [7, 8, 10, 11, 12, 13, 15, 136, 144, 146, 147, 186, 187, 193, 194, 195, 197, 204, 224, 273, 279, 282], "monitor": [7, 8, 10, 11, 12, 13, 15, 19, 136, 137, 138, 139, 142, 146, 147, 186, 187, 193, 194, 195, 197, 204, 222, 224, 228, 235, 237, 254, 279, 282], "recur": [8, 9, 12, 13, 19, 106, 136, 137, 138, 139, 187, 191, 195, 197, 214, 222, 224, 228, 235, 237, 247, 248, 264], "tempor": [8, 9, 10, 11, 12, 13, 18, 28, 31, 32, 40, 62, 79, 86, 88, 89, 90, 91, 92, 95, 97, 98, 100, 103, 104, 116, 127, 136, 138, 139, 187, 190, 191, 192, 193, 194, 195, 196, 197, 210, 214, 215, 223, 224, 225, 229, 230, 232, 233, 234, 235, 236, 237, 238, 240, 242, 243, 244, 245, 246, 260, 261, 276, 277, 278, 280], "locat": [8, 10, 15, 145, 187, 193, 196, 204, 274], "repetit": [8, 136, 143, 187, 224, 263], "natur": [8, 9, 123, 138, 145, 187, 191, 235, 268, 269, 274, 280], "phenomena": [8, 11, 13, 139, 187, 194, 197, 237], "over": [8, 18, 80, 119, 136, 138, 139, 142, 143, 187, 196, 213, 215, 223, 224, 235, 237, 254, 263], "time": [8, 9, 11, 12, 13, 18, 24, 26, 28, 30, 32, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 137, 138, 139, 140, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 187, 188, 189, 191, 192, 194, 195, 196, 197, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 215, 216, 217, 218, 220, 221, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 251, 252, 254, 256, 257, 258, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "space": [8, 12, 24, 26, 27, 29, 30, 31, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 187, 188, 189, 190, 192, 195, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "while": [8, 11, 43, 64, 66, 69, 75, 82, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 158, 159, 187, 194, 198, 200, 201, 208, 216, 217, 218, 227, 229, 230, 231, 232, 233, 236, 240, 241, 242, 243, 244, 248, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 281, 283, 285], "entiti": [8, 187], "flow": [8, 143, 187, 263], "studi": [8, 187], "character": [9, 14, 15, 18, 138, 191, 203, 204, 215, 235], "seri": [9, 11, 18, 28, 30, 93, 97, 106, 137, 140, 191, 194, 215, 223, 227, 228, 242, 247, 248], "product": [9, 191, 280], "among": [10, 193], "It": [10, 11, 19, 24, 27, 28, 30, 35, 39, 40, 43, 45, 46, 49, 66, 79, 82, 86, 89, 90, 92, 97, 98, 101, 103, 104, 106, 113, 119, 123, 131, 133, 135, 142, 152, 153, 159, 166, 178, 181, 193, 194, 196, 200, 210, 216, 222, 232, 233, 234, 238, 239, 240, 243, 245, 246, 248, 254, 258, 266, 267, 268, 269, 271, 272, 280, 283, 285], "analyz": [10, 11, 19, 142, 161, 193, 194, 222, 254], "coordin": [10, 193], "timestamp": [10, 32, 46, 82, 86, 88, 97, 101, 116, 127, 139, 181, 190, 193, 196, 216, 223, 225, 231, 237, 238, 241, 242, 260, 264, 276, 278, 280], "possibl": [10, 106, 193, 248], "relat": [10, 106, 119, 139, 147, 193, 237, 248, 282], "servic": [10, 15, 145, 193, 204, 274], "conserv": [10, 13, 193, 197], "tourism": [10, 193], "hospit": [10, 193], "sequenti": [11, 30, 39, 113, 120, 194, 214, 254, 256, 257, 258], "preserv": [11, 194], "order": [11, 54, 60, 73, 79, 80, 119, 142, 185, 194, 205, 211, 213, 223, 254, 255, 264], "instanc": [11, 119, 142, 194, 254], "transport": [11, 13, 147, 194, 197, 282], "urban": [11, 13, 15, 145, 147, 194, 197, 204, 274, 282], "plan": [11, 13, 15, 16, 145, 147, 194, 197, 204, 209, 274, 282], "alwai": [12, 195, 264], "entir": [12, 19, 195, 222, 280], "interest": [12, 78, 79, 80, 116, 195, 210, 260, 261], "In": [12, 24, 30, 39, 45, 75, 113, 116, 119, 121, 123, 127, 131, 135, 139, 145, 147, 149, 152, 153, 162, 195, 196, 208, 223, 237, 257, 261, 264, 270, 274, 277, 280, 282, 283, 286], "word": [12, 113, 195, 196, 223, 256, 258, 264], "agricultur": [12, 17, 195, 212], "crop": [12, 195], "public": [12, 54, 185, 195], "health": [12, 195], "surveil": [12, 195], "disast": [12, 17, 145, 195, 212, 274], "describ": [13, 197, 276], "consist": [13, 14, 17, 18, 143, 190, 197, 203, 212, 215, 263, 276, 280], "activ": [13, 120, 197], "area": [13, 197], "interv": [13, 18, 19, 28, 82, 136, 137, 138, 139, 140, 143, 197, 215, 216, 217, 218, 222, 224, 228, 235, 237, 247, 263], "reveal": [13, 197], "movement": [13, 197], "human": [13, 197], "logist": [13, 197], "infrastructur": [13, 197], "transact": [14, 24, 26, 27, 28, 29, 30, 31, 32, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 141, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 203, 205, 206, 207, 208, 210, 211, 213, 214, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 253, 254, 255, 256, 257, 258, 260, 261, 262, 263, 264, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "databas": [14, 16, 24, 26, 27, 28, 29, 30, 31, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 136, 138, 139, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 203, 205, 206, 207, 208, 209, 210, 211, 213, 214, 216, 220, 221, 223, 224, 225, 226, 227, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 263, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 280, 281, 283, 285], "contribut": [14, 16, 17, 141, 203, 209, 212, 253], "significantli": [14, 17, 141, 203, 212, 253], "reflect": [14, 15, 17, 203, 204, 212], "domain": [14, 15, 17, 203, 204, 212], "georeferenc": [15, 204], "combin": [15, 45, 46, 66, 86, 88, 92, 103, 104, 108, 148, 165, 181, 196, 200, 204, 226, 231, 234, 245, 246, 251, 284], "distribut": [15, 17, 30, 39, 49, 101, 176, 204, 212], "lb": [15, 204], "develop": [15, 145, 204, 274], "The": [16, 24, 26, 27, 29, 30, 31, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 136, 139, 140, 148, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 209, 210, 211, 213, 216, 217, 218, 220, 221, 224, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 284, 285], "hupm": [16, 20, 209, 219], 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257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "float": [24, 26, 27, 28, 30, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "minallconf": [24, 52, 95, 152, 153, 183, 236], "sep": [24, 26, 27, 29, 30, 31, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "t": [24, 26, 27, 30, 31, 32, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 190, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "sourc": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 39, 40, 41, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "_correlatedpattern": [24, 152, 153], "descript": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 280, 281, 283, 285], "fundament": [24, 43, 45, 48, 49, 69, 84, 88, 91, 93, 97, 100, 101, 106, 113, 121, 123, 131, 133, 152, 153, 158, 159, 162, 163, 165, 166, 174, 178, 201, 220, 227, 229, 230, 231, 238, 239, 240, 241, 242, 244, 248, 256, 257, 258, 266, 267, 268, 269, 271, 272, 283, 285], "algorithm": [24, 26, 33, 43, 45, 46, 48, 49, 50, 52, 54, 60, 64, 66, 69, 71, 75, 76, 78, 79, 80, 82, 84, 86, 89, 90, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 198, 200, 201, 202, 206, 207, 208, 210, 211, 216, 217, 218, 220, 221, 225, 226, 227, 232, 233, 234, 236, 239, 240, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 278, 281, 283, 285], "correl": [24, 52, 95, 152, 153, 154, 182, 183, 190, 214, 235, 236, 264, 265], "fp": [24, 28, 43, 45, 49, 131, 152, 153, 159, 166, 178, 283], "growth": [24, 48, 49, 75, 82, 86, 90, 97, 100, 113, 127, 152, 153, 174, 178, 208, 216, 225, 233, 242, 244, 258, 278], "depth": [24, 46, 82, 89, 98, 113, 119, 152, 153, 181, 216, 217, 218, 232, 243, 256, 258], "first": [24, 45, 46, 49, 75, 80, 82, 86, 89, 98, 110, 113, 119, 152, 153, 162, 178, 181, 206, 213, 216, 217, 218, 223, 225, 232, 243, 252, 256, 257, 258, 264, 276], "search": [24, 43, 45, 46, 49, 54, 56, 58, 62, 75, 76, 82, 84, 89, 98, 113, 119, 121, 131, 133, 152, 153, 158, 159, 162, 166, 176, 177, 178, 181, 185, 188, 189, 192, 214, 216, 217, 218, 221, 232, 243, 256, 257, 258, 283, 285], "lee": [24, 97, 127, 152, 153, 239, 277], "y": [24, 32, 33, 43, 45, 71, 97, 104, 116, 117, 119, 120, 152, 153, 159, 166, 202, 238, 246, 261, 262], "kim": [24, 152, 153], "w": [24, 79, 116, 127, 152, 153, 211, 260, 277], "cao": [24, 152, 153], "d": [24, 152, 153, 255, 264, 265], "han": [24, 43, 45, 84, 113, 152, 153, 158, 159, 166, 220, 258], "j": [24, 43, 45, 46, 48, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 91, 97, 110, 113, 116, 119, 120, 123, 127, 131, 152, 153, 159, 166, 174, 181, 202, 205, 206, 211, 213, 216, 217, 218, 220, 225, 231, 232, 240, 252, 256, 257, 258, 260, 266, 277, 283], "2003": [24, 45, 152, 153, 164], "icdm": [24, 123, 152, 153, 270], "pp": [24, 45, 49, 56, 62, 69, 79, 80, 93, 97, 110, 116, 129, 131, 133, 152, 153, 162, 176, 188, 192, 201, 210, 213, 227, 242, 252, 260, 281, 283, 285], "581": [24, 152, 153], "584": [24, 152, 153], "paramet": [24, 26, 27, 28, 29, 31, 32, 33, 35, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 272, 275, 277, 278, 281, 283, 285], "name": [24, 26, 27, 28, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 281, 283, 285], "input": [24, 26, 27, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "file": [24, 26, 27, 28, 29, 30, 31, 32, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "complet": [24, 26, 28, 29, 30, 31, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 224, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 281, 283, 285], "ofil": [24, 26, 27, 28, 29, 30, 31, 32, 35, 37, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "output": [24, 26, 27, 28, 29, 30, 31, 32, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "store": [24, 26, 27, 29, 30, 31, 33, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "user": [24, 26, 27, 28, 29, 31, 37, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 139, 142, 143, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 254, 256, 257, 258, 260, 261, 262, 263, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "specifi": [24, 29, 32, 33, 37, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "either": [24, 29, 40, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 280, 281, 283, 285], "count": [24, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 110, 113, 116, 117, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "proport": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 136, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 224, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "size": [24, 29, 30, 32, 33, 39, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "If": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 190, 192, 198, 200, 201, 202, 205, 207, 210, 211, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 281, 283, 285], "program": [24, 26, 29, 30, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "integ": [24, 29, 30, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 78, 79, 80, 82, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 207, 210, 211, 216, 223, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 248, 252, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "treat": [24, 29, 43, 45, 46, 48, 49, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 106, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 181, 183, 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174, 178, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 220, 221, 225, 227, 229, 230, 231, 233, 234, 236, 238, 239, 240, 241, 242, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "mapsupport": [24, 43, 45, 46, 48, 84, 86, 88, 90, 91, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 166, 174, 181, 220, 221, 226, 227, 229, 230, 231, 233, 236, 238, 239, 240, 241, 242, 244, 248, 251, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "dictionari": [24, 26, 27, 30, 31, 39, 43, 45, 46, 48, 49, 50, 54, 64, 66, 69, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 185, 198, 200, 201, 205, 211, 213, 216, 220, 221, 225, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "maintain": [24, 43, 45, 46, 48, 49, 82, 84, 86, 88, 90, 91, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 166, 174, 178, 181, 216, 220, 221, 225, 226, 227, 229, 230, 231, 233, 236, 238, 239, 240, 241, 242, 244, 248, 251, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "lno": [24, 43, 48, 49, 84, 86, 88, 90, 91, 93, 95, 97, 100, 101, 104, 106, 108, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 174, 176, 177, 178, 220, 221, 226, 227, 229, 230, 231, 233, 236, 238, 239, 240, 241, 242, 244, 246, 248, 251, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 278, 281, 283, 285], "tree": [24, 43, 45, 46, 48, 49, 71, 73, 75, 79, 80, 82, 84, 86, 88, 90, 91, 93, 95, 97, 100, 101, 106, 108, 110, 116, 117, 123, 125, 127, 129, 131, 133, 135, 152, 153, 159, 166, 174, 178, 181, 202, 205, 206, 208, 211, 213, 216, 220, 221, 225, 227, 229, 230, 231, 233, 236, 238, 239, 240, 241, 242, 244, 248, 251, 252, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "itemsetcount": [24, 46, 48, 90, 93, 95, 97, 100, 101, 106, 108, 116, 117, 123, 125, 127, 135, 152, 153, 174, 181, 227, 233, 236, 238, 239, 240, 241, 242, 244, 248, 251, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 278], "finalpattern": [24, 26, 31, 43, 45, 46, 48, 49, 50, 64, 66, 69, 78, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 198, 200, 201, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "dict": [24, 26, 27, 30, 31, 33, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "itemsetbuff": [24, 54, 56, 58, 60, 62, 108, 152, 153, 185, 188, 189, 251], "maxpatternlength": [24, 108, 152, 153, 251], "constraint": [24, 73, 79, 101, 108, 110, 113, 116, 139, 143, 152, 153, 205, 211, 237, 251, 252, 256, 257, 258, 260, 261, 263], "length": [24, 27, 30, 32, 39, 40, 43, 75, 79, 82, 108, 113, 121, 123, 125, 127, 135, 152, 153, 158, 207, 210, 216, 217, 218, 251, 256, 257, 258, 266, 267, 268, 269, 270, 271, 272, 275, 278], "termin": [24, 26, 45, 46, 50, 56, 93, 97, 98, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 179, 181, 188, 227, 238, 239, 243, 266, 267, 268, 269, 270, 272, 275, 277, 278, 281, 283, 285], "command": [24, 26, 45, 46, 50, 56, 93, 97, 98, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 179, 181, 188, 227, 238, 239, 243, 266, 267, 268, 269, 270, 272, 275, 277, 278, 281, 283, 285], "format": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 120, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "venv": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 88, 89, 91, 93, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 227, 230, 231, 232, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 266, 267, 268, 269, 270, 272, 275, 277, 278, 281, 283, 285], "python3": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "py": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "inputfil": [24, 26, 27, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "outputfil": [24, 26, 27, 28, 30, 32, 35, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "exampl": [24, 26, 30, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 190, 192, 196, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 223, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 255, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 276, 277, 278, 280, 281, 283, 285], "sampletdb": [24, 26, 48, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 89, 90, 93, 95, 97, 98, 100, 101, 106, 110, 116, 117, 123, 125, 127, 135, 152, 153, 155, 156, 174, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 227, 232, 233, 236, 240, 241, 242, 243, 244, 248, 252, 260, 261, 262, 266, 271, 275, 277, 278], "txt": [24, 26, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "25": [24, 152, 153], "2": [24, 40, 48, 50, 52, 54, 56, 58, 60, 62, 69, 73, 79, 80, 88, 89, 91, 97, 98, 100, 106, 108, 113, 116, 121, 127, 129, 152, 153, 174, 179, 183, 185, 188, 189, 190, 192, 196, 201, 205, 211, 213, 223, 229, 230, 232, 240, 241, 242, 243, 244, 248, 251, 256, 258, 260, 264, 265, 276, 277, 278, 280, 281], "call": [24, 26, 45, 46, 50, 56, 58, 78, 80, 82, 97, 98, 113, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 162, 163, 164, 165, 166, 179, 181, 188, 189, 218, 238, 239, 243, 256, 257, 266, 267, 268, 269, 270, 275, 276, 277, 278, 281, 283, 285], "alg": [24, 26, 30, 39, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "obj": [24, 26, 27, 28, 29, 30, 31, 32, 33, 35, 37, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "getpattern": [24, 26, 29, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "print": [24, 26, 28, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "number": [24, 26, 30, 32, 39, 40, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 264, 265, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 280, 281, 283, 285], "len": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 79, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "savepattern": [24, 45, 46, 48, 75, 76, 84, 101, 104, 106, 110, 113, 117, 120, 125, 127, 131, 152, 153, 164, 166, 174, 181, 221, 246, 248, 252, 256, 257, 258, 262, 275, 278, 283], "df": [24, 26, 28, 43, 45, 46, 48, 49, 50, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 119, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "getpatternsasdatafram": [24, 26, 43, 45, 46, 48, 49, 50, 52, 54, 56, 58, 60, 62, 64, 66, 69, 71, 73, 75, 76, 78, 79, 80, 82, 84, 86, 88, 89, 90, 91, 92, 93, 95, 97, 98, 100, 101, 103, 104, 106, 108, 110, 113, 116, 117, 121, 123, 125, 127, 129, 131, 133, 135, 152, 153, 155, 156, 158, 159, 162, 163, 164, 165, 166, 174, 176, 177, 178, 179, 181, 183, 185, 188, 189, 192, 198, 200, 201, 202, 205, 206, 207, 208, 210, 211, 213, 216, 217, 218, 220, 221, 225, 226, 227, 229, 230, 231, 232, 233, 234, 236, 238, 239, 240, 241, 242, 243, 244, 245, 246, 248, 251, 252, 256, 257, 258, 260, 261, 262, 266, 267, 268, 269, 270, 271, 272, 275, 277, 278, 281, 283, 285], "memuss": [24, 26, 28, 43, 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